4.665 Empregos para Modelagem Preditiva - Brasil

Overview:

Job Title: Senior Full-stack Engineer

Work Arrangement: Remote| Must be able to work EST hours

Job Type: Full-time

Salary: Competitive base salary in USD

Industry: PropTech / B2B SaaS / Real Estate Technology

Work Schedule: 40 hours per week

About Pearl Talent:

Pearl works with the top 1% of candidates from around the world and connects them with the best startups in the US and EU. Our clients have raised over $5B in aggregate and are backed by companies like OpenAI, a16z, and Founders Fund. They're looking for the sharpest, hungriest candidates who they can consistently promote and work with over many years. Candidates we've hired have been flown out to the US and EU to work with their clients, and even promoted to roles that match folks onshore in the US.

Hear why we exist, what we believe in, and who we're building for: Watch here

Why Work with Us? :

We're not just another recruiting firm—we focus on placing candidates with exceptional US and EU founders who prioritize the long-term success of their team members. We also provide retention bonuses at 3, 6, 9, and 12 months, as well as community-driven benefits like an annual retreat.

About the company:

Our partner company helps the world's most prominent companies navigate their most important brand, reputation, and product challenges. We specialize in high-impact research with hard-to-reach audiences -- recruiting the exact audiences our clients need, anywhere in the world. Our in-house teams ensure rigorous quality, rapid execution, and clear, strategic insights. Every engagement is custom-built, senior-led, and designed to deliver answers that drive key decisions.

Key Responsibilities

• Train and evaluate ML models using common machine learning frameworks in Python. Examples include TensorFlow, Keras, scikit-learn, or PyTorch.
• Develop and refine NLP pipelines (e.g., tokenization, entity recognition, similarity models).
• Perform fine-tuning and prompt engineering for LLMs (GPT, Claude, etc.).
• Create semantic search and recommendation models using vector embeddings and clustering techniques.
• Conduct experiments, hyperparameter tuning, and performance benchmarking.
• Collaborate with software engineers to integrate models into backend systems.
• Prepare clear documentation, model cards, and evaluation reports.

Requirements:

Required Skills

• Strong proficiency in Python for machine learning and data processing.
• Experience with NLP libraries: spaCy, Hugging Face Transformers, gensim, nltk.
• Comfortable training deep learning models using Keras, TensorFlow, or PyTorch.
• Ability to design and execute ML experiments, evaluate models, and interpret results.
• Familiar with version control (Git), shell scripting, and Linux development environments.
• Basic back end software engineering skills, such as creating and managing endpoints, database services, and task queues.
• Experience with production environments (e.g., batch inference, model packaging).

Nice to Have

• Experience with MLOps tools (e.g., MLflow, SageMaker, DVC).
• Contributions to Kaggle competitions, AI research, or open-source ML/NLP projects.
• Background in classical ML, unsupervised learning, or semantic modeling.

Working Conditions

• Fully remote, must be able to collaborate during EST hours.
• Work closely with backend/frontend engineers, but not expected to build application UIs.
• Focused environment for pure AI/ML development, research, and delivery.

Benefits:

Why Join Now

• Be a foundational member of a venture-scale company with real distribution advantages in real estate.
• Own key technical systems from day one, shaping how they evolve.
• Culture built on speed, iteration, and execution.

What You'll Get:

• Professional Development: Annual learning budget for books, courses, and conferences
• Mentorship: Learn directly from startup veterans (ex-Looker, GitHub, Mulesoft)
• Impact: Help shape a growing brand with a voice that influences fintech innovation
• Inspiring Workspaces: Offices in Berlin, New York, and London, with travel opportunities
• Flat Hierarchy: Work directly with founders and have your ideas heard
• Flexible Work Setup: Equipment of your choice, strong home office support

Hiring Process:

• Application
• Screening
• Top-grading Interview
• Skills Assessment
• Client Interview
• Offer
• Onboarding

Lateral stands for technology excellence.

We’re a profitable, award-winning design and technology company with over 20 years of experience launching bold ventures and transforming businesses. A globally distributed team of 200+ experts united by a shared purpose: the continuous pursuit of quality.

Our clients come to us for results, quality and craft - and stay because we keep raising the bar.

Our mission is simple:design and build great products .
What sets us apart isn’t just the talent of our team -it’sthe way we work:

We Have A Bias For Action & Results.

We are doers - we spot the gaps, connect the dots, anticipate what’s around the corner and take action. We move fast, stay focused, and let the results -not the effort -speak for themselves.

We Work On Time, On Budget, On Quality

Discipline is our edge - a commitment we make to each other, to our clients, and to the standards we hold ourselves to.

We Care Deeply.

We care about our work and about each other. Care Is A Competitive Advantage.

Every detail matters. Every design, every line of code, every decision. Thoughtful by default.

We Do Things Right -Because It’s the Right Thing to Do

Right over easy. Integrity isn’t up for negotiation. We hold the bar high even when no one’s watching. We take pride in doing great work the right way -not the easy way.

We Keep Improving

The best teams keep improving and we’re never done learning.

We iterate. We reflect on what’s working and what’s not. Feedback fuels us, we receive it openly, and adapt quickly. Progress over perfection.

We’re Obsessed With Agility, Not The Agile Manifesto

We don’t chase dogma or rituals -we chase momentum. We adapt processes to fit problems, not the other way around.

We Take Ownership
Everyone leads something here. You will have room to run with ideas, and the trust to execute. That trust is built on how you show up: thinking things through, sweating the details, and following through.

We leverage cutting-edge machine learning to deliver innovative solutions in medical imaging. As a Machine Learning Engineer at Lateral, you will be instrumental in realizing our AI vision through a variety of critical tasks:

• Experimentation and Optimization: You will help parallelize and distribute work amongst different experiment tracks, optimize model performance via hyperparameter tuning, model ensembling, or advanced training strategies, and design and conduct systematic experiments to validate hypotheses and model improvements.

• Research and Development: Your responsibilities will include conducting literature reviews on state-of-the-art methods in medical imaging, designing and prototyping novel machine learning models, implementing model architecture and training strategies in code, and generating ideas and exploring methods for improvements to existing models or tasks.

• Analysis and Validation: You will perform statistical analysis to assess model robustness and reproducibility, and compare proposed methods against baselines and benchmarks from existing literature.

• Interdisciplinary Collaboration: You will collaborate with domain experts to define problem statements and interpret model outputs, ensuring our AI solutions are both technically sound and clinically impactful.

We’re seeking research-minded engineers who are excited to build real, meaningful ML systems, not just prototypes. You’ll thrive in this role if you bring:

• 2+ years of hands-on experience in machine learning, including model design, training, and evaluation.

• Demonstrated experience applying machine learning to real-world computer vision problems, including developing, deploying, and optimizing models.

• Familiarity with deep learning frameworks such as PyTorch or TensorFlow and comfort writing clean, modular experimentation code.

• Practical experience running experiments, tuning models, and comparing approaches via systematic validation.

• Excellent grasp of modern ML concepts: regularization, loss functions, optimization strategies, generalization, overfitting, etc.

• Basic data analysis skills using tools like Polars or Pandas for efficient data manipulation and exploratory data analysis.

• An understanding of statistical testing and experimental design to assess performance, robustness, and reproducibility.

• Curiosity about new techniques — you enjoy staying current with ML literature and applying ideas in production-minded ways.

• Strong communication skills — able to collaborate with other engineers, researchers, and domain experts to translate needs into solutions.

Bonus points for:

• Experience with medical imaging, scientific ML, or regulated environments.

• Contributions to papers, open-source projects, or research infrastructure.

• Familiarity with explainability techniques (e.g., SHAP, saliency maps) and fairness/audit frameworks.

• A track record of generating novel ideas, exploring them rigorously, and translating them into working systems.

• Experience building ML pipelines (training, evaluation, deployment) in production, especially in cloud environments like AWS.

• Real Impact: You’ll work on meaningful products that make a measurable difference - from healthcare and commerce to sustainability and next-gen tech.
  
  

• Remote-First, Office Friendly: Work from wherever you’re most productive - whether that’s your home, a co-working space, or one of our offices. We’re a remote-first company, but if you’re near an office, you’re welcome to drop in, collaborate in person, or work onsite regularly.
  
  We prioritize async collaboration, respect your time zone, and focus on outcomes over hours.
  
  

• An Outstanding Team: Talented, kind, and hard-working people who care deeply about their craft - and about each other. No egos. No politics. Just professionals doing their best work.
  
  

• Growth: You’ll be supported in growing your craft, exploring new paths, and stepping into greater responsibility -at your own pace
  
  

• A Culture of Excellence: We care deeply about doing the right thing -for our clients, our team, and ourselves. No burnout. No crunch. Just high-quality work, delivered sustainably.
  
  

• Variety & Stability: We’re profitable, independent, and over a decade strong. Yet every project brings a fresh challenge. You’ll never be bored here.

We want to respect your time by being clear about what this role isn’t. You should skip this opportunity if:

• You prefer well defined structure. If you gravitate towards a clear hierarchy, well defined roles and swim lanes, you may find our self-managed style challenging.
  
  

• Distributed work isn’t your thing. If you find async communication, design documentation and being proactive without a manager nearby difficult, our setup won’t suit you.
  
  

• Feedback doesn't excite you. We’re obsessed with quality and believe in continuous improvement. That means we give feedback that’s sometimes nitpicky. If refining the work until it’s excellent feels over the top, you are likely going to find working here frustrating.
  
  

• Change makes you uncomfortable. We’re scaling and maturing. That means not everything is perfect yet. Priorities shift. Processes evolve. If ambiguity is uncomfortable, this may feel bumpy.
  
  

However, If this sounds like fuel, we’d love to talk!

Our hiring process is structured as a sequence of steps. Moving forward is based on how well the previous step goes. This helps us stay focused, fair, and respectful of everyone’s time.

We will always:

• Let you know clearly what the next step is

• Share updates and feedback wherever possible

• Invite questions if anything feels unclear

Not everyone progresses through every stage. That doesn’t mean you’re not great at what you do. Sometimes it’s about timing, team fit, or simply what we’re looking for at the moment.

If this sounds like your kind of team and you’re ready to bring your craft to Lateral, we want to hear from you.

Please send us:

• Yourresume

• Ashort note about what excites you about this role

• Links to your work : GitHub/ Code snippets, portfolio, architecture /design docs, blog posts, oranything that shows us how you think and build
  
  Please don’t include anything sensitive or proprietary.
  If you’re sharing team projects, let us know what your specific contributions were.

We review every application with care. If there’s a fit, we’ll reach out to schedule next steps.

Purpose: A structured discussion with our People Experience team to delve into your career trajectory, motivations, and alignment with Lateral's values.

What to Expect:

• In-depth questions about your past experiences and decision-making processes.

• Exploration of your career goals and how they align with the role.

• Discussion about our company culture, availability, compensation and other logistics

• Motivators and demotivators.

• Your life outside coding.

Preparation Tips:

• Reflect on your career journey and pivotal moments.

• Be ready to discuss challenges you've overcome and lessons learned.

• Familiarize yourself with the Job Description, Lateral's mission and values.

Purpose: Assess your technical proficiency and problem-solving abilities.
Format: A collaborative session with our engineering team, focusing on real-world scenarios relevant to the role.

What to Expect:

• Problem-solving exercises/questions that mirror tasks you'd encounter in the position.

• Discussions around your approach, reasoning, and solutions.

Preparation Tips:

• Practice articulating your thought process clearly and concisely.

• Be prepared to discuss in depth past projects and the technologies used.

Purpose: Evaluate how well you collaborate, communicate, and consult with external stakeholders.

Format: A live conversation with one of our client-side collaborators

What to Expect:

• Discussion around business and technical challenges from the client’s perspective.

• Opportunity to explain your approach, gather requirements, ask clarifying questions, and articulate tradeoffs.

• Evaluation of how clearly you communicate solutions to both technical and non-technical stakeholders.

Preparation Tips:

• Once client details are shared, educate yourself with their business and potential challenges

• Review past experiences where you’ve had to communicate complex ideas clearly.

• Reflect on your ability to lead conversations, guide decision-making, and build trust across different audiences.

Purpose: Understand your approach to prioritizing, collaborating, shipping, and iterating.

What to expect:

• How you prioritize and break down work.

• How you collaborate across disciplines.

• How you handle blockers, feedback, and iteration.

Preparation Tips:

• Pick 1-2 meaningful projects you led or heavily contributed to.

• Walk through your process: what worked, what didn’t, what you’d do differently.

• Think about how you manage time, scope, and changing requirements.

Purpose: We believe references are about understanding, not just validation. We do not look for perfection, but to understand patterns, strengths, and context. We use them to learn how to support you best.

What to Expect: we’ll ask you for 2–3 people who’ve worked closely with you. These are often: former managers, senior peers or collaborators, mentors or people you've mentored.

What we ask: We focus on how you’ve grown, where you shine, how you like to be led, and what support sets you up for success. We want practical advice for making this a great fit for you.

Yes, we do backchannels too: We do thiswhen we feel we need more context . We will check with you if there are folks we should avoid reaching out due to confidentiality or other reasons. Andhere’s our commitment: if anything surprising or unclear comes up in a backchannel, we’ll bring it directly to you. We believe in “no stories without you in the room .” You’ll always get the chance to share your side, context, or clarification.

What Happens: If selected, you'll receive a comprehensive offer detailing compensation, and other pertinent information.

Our hiring process is designed to be thorough yet respectful, ensuring a mutual fit. We encourage candidates to engage actively, ask questions, and view this as a two-way exploration.

Join us and let’s build something extraordinary.

Remoto - Modelo PJ

Machine Learning Engineer Sr. (1 vaga)

Requisitos:

• Experiência sólida em deploy de modelos de ML em produção.

• Python avançado + frameworks (Scikit-learn, TensorFlow, PyTorch).

• Vivência com MLFlow, Databricks e CI/CD para modelos.

Interessados, entrem em contato ou enviem o currículo diretamente para

Company overview:
Blue Orange Digital is a boutique data & AI consultancy that delivers enterprise-grade results. We design and build modern data platforms, analytics, and ML/AI Agent solutions for mid‑market and enterprise clients across Private Equity, Financial Services, Healthcare, and Retail.

Our teams work with technologies like Databricks, Snowflake, dbt, and the broader Microsoft ecosystem to turn messy, real-world data into trustworthy, actionable insight.

We're a builder‑led, client‑first culture that prizes ownership, clear communication, and shipping high‑impact work.

Position overview:
Blue Orange is seeking to expand our Team of expert consultants with an experienced Machine Learning Engineer to address a set of expanding opportunities in the next several months. The ideal candidate will possess a deep passion for machine learning, AI tech and innovative data solutions with proficiency in advanced machine learning techniques, strong skills in programming languages such as Python, expertise around data analytics and feature engineering, experience working with some of the main ML and D frameworks, a proven track record of working with cloud-native solutions in at least 1 of the main clouds (AWS, GCP, Azure, or Snowflake, etc.), MLOps and LLMs, and strong proficiency in the end-to-end ML/AI cycle, from ideation to production. The candidate will play a crucial role in driving our machine-learning initiatives forward. The candidate will have excellent communication skills to collaborate with technical and non-technical stakeholders effectively.

At Blue Orange, you'll have the opportunity to work on cutting-edge projects, leveraging modern machine-learning and AI techniques to deliver tangible business outcomes and drive innovation in our data-driven solutions.

Note:
Please submit your resume in English, as all application materials must be in English for review and consideration.

Responsibilities:

• Collaborate with cross-functional teams to understand business requirements and design to productionize Gen AI solutions into practical product driven applications.
• Design and implement application integrations to leverage newly build GenAI Products.
• Build solutions that improve delivery speed and scalability of product pipelines.
• Leverage managed and serverless cloud offerings to create performant and scalable cloud native application solutions and data pipelines.
• Experiment with retrieval-augmented generation (RAG) approaches to improve the relevance and coherence of AI-generated outputs.
• Work closely with GenAI engineers and researchers to integrate prompt engineering and RAG components into production systems and ensure seamless deployment.
• Stay up to date with the latest advancements in prompt engineering, RAG, data science, machine learning, and AI technologies, and explore innovative approaches to enhance Gen AI capabilities.

Requirements:

• Experience with NLP and LLM-based technologies and frameworks.
• Proficiency in programming languages such as Python and JavaScript is preferred.
• Proven track record of successful delivery of software engineering projects.
• Ability to think and learn on your feet, and the ability to quickly become proficient with new technologies in a fast-paced environment.
• Understanding and passion for Test Driven Design.
• Familiarity with ETL concepts and best practices.
• Experience with prompt engineering and RAG techniques preferred.
• Excellent problem-solving skills, critical thinking abilities, and attention to detail.
• Effective communication skills and the ability to collaborate effectively in a team environment.
• Passion for AI and a desire to contribute to the advancement of Gen AI technologies.
• Strong problem-solving and analytical skills.
• Self-driven and autonomous.
• Excellent verbal and written communication skills.
• Team player.
• Eagerness to learn and adapt in a fast-paced environment.
• 5+ years of industry experience as a hands-on practitioner of software engineering and proven experience with cloud offerings.
• 3+ years of experience with cloud platforms such as AWS.
• Experience with Docker preferred.
• Bachelor's degree or higher in Computer Science or a related field.

Preferred qualifications:

• Advanced degree in a relevant field.
• Publications in relevant AI/ML communities and journals.
• Experience fine-tuning OpenSource LLMs and deploying them.
• MLFlow, etc., a plus.

Benefits:

• Fully remote
• Flexible Schedule
• Unlimited Paid Time Off (PTO)
• Paid parental/bereavement leave
• Worldwide recognized clients to build skills for an excellent resume
• Top-notch team to learn and grow with

Salary:
USD $7,454 - $9,486 (monthly salary range)

Background checks may be required for certain positions/projects.

Blue Orange Digital is an equal opportunity employer.

Ambush is a people-first company. We believe that our success is built on the talent and dedication of our team. We take a human-centered approach to everything we do, from recruiting top-tier remote professionals to fostering a collaborative and supportive work environment.

Since 2015, we've been growing our consulting business by delivering exceptional quality work to our clients. We're not afraid to take risks and always strive to find the best solution, not just the easiest one. Our highly skilled team of engineers is committed to using their expertise to tackle every challenge with passion and precision.

Teamwork is at the heart of everything we do. We believe in the power of collaboration, knowledge sharing, and mutual support. At Ambush, you'll find a dynamic environment where you're encouraged to grow, learn, and share your expertise with your colleagues. We offer various initiatives to help you enhance your skills and broaden your knowledge base.

If you're a team player who's driven to achieve great things and passionate about making a real impact, we want you on our team.

When you join us, you will:

• Ensure that data flows smoothly from source to destination so that it can be processed
• Utilize strong database skills to work with large, complex data sets to extract insights
• Filter and cleanse unstructured (or ambiguous) data into usable data sets that can be analyzed to extract insights and improve business processes
• Identify new internal and external data sources to support analytics initiatives and work with appropriate partners to absorb the data into new or existing data infrastructure
• Build tools for automating repetitive asks so that bandwidth can be freed for analytics
• Collaborate with program managers and business analysts to help them come up with actionable, high-impact insights across product lines and functions
• Work closely with top management to prioritize information and analytic needs

What we'd like to see in a candidate:

• Strong expertise in Machine Learning (ML) with experience applying it to real-world problems.
• Deep understanding and previous experience with Generative AI (GenAI), Large Language Models (LLMs), and their applications in complex systems (RAG, Embeddings, LLM/VLM deployment, LLM/VLM fine tuning).
• Experience working with traditional Convolutional Neural Networks (CNNs).
• Knowledge or previous experience working with Amazon Bedrock.
• Background in FinTech is a plus, with knowledge of financial systems, risk modeling, or fraud detection.
• Strong analytical and problem-solving skills to design scalable AI-driven solutions.
• Proficiency in software engineering best practices, including unit testing, CI/CD pipelines, and version control.
• Experience with Agile/Scrum methodologies for software development.
• Strong English communication skills, both written and verbal.
• This position may involve eventual travel opportunities to other countries, so certain availability is required.

Você é apaixonado(a) por tecnologia, inovação e quer fazer parte de um ambiente inclusivo, colaborativo e em constante evolução? Então essa oportunidade é para você

Na Capgemini, valorizamos o equilíbrio entre vida pessoal e profissional. Por isso, oferecemos modelos de trabalho flexíveis, que podem variar entre home office, híbrido ou presencial, de acordo com as necessidades do projeto. Nosso objetivo é proporcionar a melhor experiência para você, respeitando seu estilo de vida e promovendo bem-estar.

Estamos em busca de um(a) Machine Learning Engineer, com foco em AWS & Dataiku, para compor nosso time.

• Responsável por liderar a modernização de pipelines de dados e modelos de machine learning, migrando soluções existentes em Dataiku para uma arquitetura robusta e escalável na AWS.
• Analisar o projeto atual em Dataiku e mapear os fluxos de dados, pipelines e modelos existentes.
• Redesenhar e migrar pipelines para arquitetura AWS (Glue, EMR, Lambda, Step Functions), otimizando performance e custos.
• Construir e orquestrar pipelines ETL/ELT escaláveis para alimentar modelos em SageMaker.
• Implementar uma pipeline completa de MLOps (Processing, Training, Model Registry, Deployment).
• Integrar boas práticas de versionamento de dados, código e modelos (Git, DVC).
• Garantir segurança e compliance (IAM, KMS, CloudWatch, CloudTrail).
• Tomar decisões técnicas de forma autônoma e apresentar soluções aos stakeholders.
• Documentar padrões de arquitetura e boas práticas para manutenção futura.

• Experiência prática com engenharia de dados (ETL/ELT, modelagem, orquestração).
• Proficiência em AWS (SageMaker, Glue, EMR, Lambda, S3, Step Functions, CloudWatch, IAM).
• Experiência sólida em MLOps e CI/CD para modelos de machine learning.
• Domínio de Python e bibliotecas como Pandas, PySpark, boto3.
• Experiência prévia com migração de plataformas de dados/ML.
• Capacidade comprovada de atuar de forma autônoma e liderar iniciativas técnicas.
• Inglês avançado.

• Experiência com Dataiku ou projetos similares de migração.
• Conhecimento em IaC (Terraform, CloudFormation).
• Vivência com monitoramento e logging de pipelines de ML.
• Experiência em ambientes ágeis e cultura DevOps.
• Espanhol avançado para conversação.

Na Capgemini, você pode ser quem você é. Valorizamos a diversidade em todas as suas formas e promovemos um ambiente inclusivo por meio de comitês como:

• – Empoderamento feminino e equidade de gênero.
• Capgemini Black – Representatividade e valorização da cultura negra.
• LGBTQIA+@Capgemini, Capgemini Accessibility, entre outros.

Nosso compromisso é contínuo: somos reconhecidos pela GPTW, Bloomberg Gender Equality Index, EDGE e Ethisphere como uma das empresas mais éticas e inclusivas do mundo. Nossas vagas são para todas as pessoas, independentemente de cor, etnia, religião, idade, identidade de gênero, orientação sexual ou deficiência.

Aqui, você é protagonista da sua carreira Oferecemos:

• Plano de carreira estruturado e trilhas personalizadas de aprendizado.
• Universidade Corporativa, com acesso a Harvard, Coursera, Udemy, Pluralsight.
• Certificações oficiais com parceiros como SAP, AWS, Microsoft, Salesforce.
• Idiomas com EF Education First (Inglês, Espanhol, Francês e Alemão).

• Assistência médica e odontológica.
• Gympass e Equilibrium (saúde física e mental).
• Previdência privada e seguro de vida.
• Programa Family Care: licenças maternidade e paternidade estendidas, apoio à fertilidade, orientação personalizada em saúde e bem-estar.
• Vale-refeição, auxílio home office, clube de benefícios e muito mais

Na Capgemini, liberamos a energia humana por meio da tecnologia para construir um futuro mais inclusivo, sustentável e inovador. Se você compartilha desses valores, venha transformar o mundo com a gente

Descrição da vaga

Os Machine Learning Engineers da Blip trabalham na implementação e otimização de soluções de inteligência artificial e machine learning aplicadas ao desenvolvimento de sistemas de IA conversacional. Trabalham em conjunto com Data Scientists e AI Engineers para alcançar objetivos comuns, contribuindo na integração de modelos de IA em APIs e aplicações em produção.

Responsabilidades e atribuições

• Trabalhar de forma colaborativa com equipes de Machine Learning Engineers, Data Scientists e AI Engineers na construção e integração de modelos avançados de IA em APIs e aplicações de produção;
• Identificar e implementar melhorias em pipelines de RAG, focando na otimização da geração e recuperação de conhecimento, com orientação mínima;
• Contribuir para a definição de estratégias e melhores práticas no desenvolvimento e implantação de modelos de IA, incluindo otimização de processos, evolução de tecnologias e análise de riscos;
• Trabalhar em estreita colaboração com as partes interessadas para garantir que os modelos e sistemas de IA atendam aos requisitos do negócio e sejam escaláveis a longo prazo;
• Realizar avaliações detalhadas de modelos de Machine Learning e soluções de IA, recomendando e implementando ajustes para melhorar a performance e a precisão dos resultados;
• Revisar código dos pares e fornecer feedbacks construtivos;
• Debugar e solucionar problemas técnicos de moderada complexidade;
• Identificar e comunicar potenciais riscos técnicos e impedimentos;
• Monitorar stack features usando ferramentas de observabilidade interna;
• Entregar pequenas funcionalidades e melhorias com mínima orientação;
• Mentorar outros membros da equipe;

Requisitos e qualificações

• 2+ anos de experiência como Machine Learning Engineer;
• Conhecimento intermediário em Machine Learning, NLP e LLMs, com experiência prática no desenvolvimento e aplicação desses modelos em ambiente de produção;
• Conhecimento intermediário de RAG (Retrieval-Augmented Generation);
• Experiência profissional em Python;
• Experiência profissional com bancos de dados vetoriais e técnicas avançadas de indexação e recuperação de dados;
• Experiência profissional na avaliação e monitoramento de modelos de ML, com habilidades para identificar e corrigir falhas de desempenho;
• Experiência profissional no desenvolvimento de APIs REST utilizando frameworks como FastAPI, incluindo a criação de endpoints robustos para integração de modelos de I.A;
• Experiência em trabalhar de forma independente e colaborativa, com forte habilidade para resolver problemas complexos e otimizar sistemas existentes;
• Experiência básica com desenho de soluções de IA com GenAI;
• Experiência básica com desenvolvimento de pipelines de dados (ETL) em ambiente de Big Data;
• Experiência básica com MLOps;
• Experiência básica com ferramentas de observabilidade como Grafana;
• Familiaridade com execução e reprodução de análises exploratórias de dados;
• Familiaridade com experimentação com soluções de GenAI (soluções Agentic, e afins);
• Experiência básica com desenho de arquitetura de soluções de IA que sejam eficientes e escaláveis.
• Conhecimento de controle de versão como Git;
• Experiência trabalhando em equipe remota;
• Mentalidade proativa de aprendizado;
• Capacidade de aceitar e incorporar feedbacks efetivamente;
• Conhecimento intermediário de Cloud (AWS, Azure ou GCP);
• Conhecimento intermediário de estrutura de pipelines de dados.

Informações adicionais

Nada Básico Que Amamos
Sua Experiência no Dia a Dia

• Horário Flexível: Mais autonomia para organizar sua rotina com equilíbrio e responsabilidade.
• Modelos de Trabalho Flexíveis: Remoto, híbrido ou presencial, conforme a necessidade da função.
• No Dress Code: Liberdade para ser quem você é, sem formalidades.
• Auxílio Home Office e Blip Setup: Suporte financeiro para montar (ou melhorar) seu espaço de trabalho remoto.
• Day Off de Aniversário: Um dia de folga no mês do seu aniversário para comemorar como quiser.
• Blip Recharge: São 5 dias de folga remunerada por ano, para cargos que não fazem registro de ponto, pensados para equilibrar a jornada.

Bem-estar e Qualidade de Vida

• Vale Alimentação ou Refeição: R$ 1.144,00 mensais, sem desconto e creditado inclusive nas férias e licenças.
• Vale Transporte: Disponível conforme necessidade de deslocamento.
• Wellhub (Gympass): Acesso a academias, apps de bem-estar e atividades físicas, também para dependentes.
• Convênio SESC: Acesso à cultura, lazer, esportes, hotéis, colônia de férias e mais.

Saúde Física e Emocional

• Plano de Saúde (Amil): Cobertura nacional, quarto privativo para você e seus dependentes, com desconto apenas de coparticipação.
• Plano Odontológico: Cobertura nacional para você e seus dependentes, com três opções de planos, e desconto integral do valor do plano escolhido.
• Conexa Saúde: Plataforma de atendimento psicológico online.
• Seguro de Vida: Cobertura equivalente a 24 vezes o seu salário mensal.

Família, Parentalidade e Apoio

• Licença Maternidade Estendida: 180 dias para viver o início dessa nova fase com tranquilidade.
• Licença Paternidade Estendida: 30 dias para estar presente e fortalecer vínculos.

PRAZER, SOMOS A BLIP

Aqui oferecemos uma experiência surpreendente, rápida e inteligente para os seus clientes, porque
Blip é o futuro
Somos a
Blip
, uma plataforma de interações inteligentes, onde as empresas se encontram com clientes em vários canais de comunicação, como WhatsApp, Instagram, Facebook ou no chat do seu site.

Aqui nós temos um time de
Blippers
que vive inovação no dia dia, com um ponto de vista único para evoluir as jornadas de comunicação, sempre com confiança para aprender mais E no nosso próprio ritmo, vamos muito mais longe

A Blip é
feita de pessoas para pessoas
Somos
especialistas, inquietos e bem-humorados
e é assim que nós entregamos conversas no ritmo das pessoas. Somos líderes de mercado na América Latina, com Blippers atuando em vários lugares do mundo, sempre com confiança para ir longe

Valorizamos pessoas em primeiro lugar e por isso consideramos todos os grupos de diversidade nas nossas vagas.
E se você é uma Pessoa com Deficiência (PcD) ou Neurodivergente, saiba que todas as vagas da Blip também são inclusivas Estamos esperando sua inscrição

Who We Are
We are a leader in fraud prevention and AML compliance. Our platform uses device intelligence, behavior biometrics, machine learning, and AI to stop fraud before it happens. Today, over 300 banks, retailers, and fintechs worldwide use Sardine to stop identity fraud, payment fraud, account takeovers, and social engineering scams. We have raised $145M from world-class investors, including Andreessen Horowitz, Activant, Visa, Experian, FIS, and Google Ventures.

Our Culture

• We have hubs in the Bay Area, NYC, Austin, and Toronto. However, we maintain a remote-first work culture. #WorkFromAnywhere
• We hire talented, self-motivated individuals with extreme ownership and high growth orientation.
• We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule.

Location:
Remote - Brazil

• To be considered for this position, you must reside in one of the following cities:

• São Paulo: São Paulo, Campinas, São José dos Campos

• Rio de Janeiro: Rio de Janeiro
• Minas Gerais: Belo Horizonte
• Paraná: Curitiba
• Santa Catarina: Florianópolis

About The Role
We're on the lookout for a Machine Learning Engineer to spearhead the evolution of our device intelligence and fingerprinting systems. This isn't just a role; it's a chance to lead groundbreaking projects that directly combat fraud and enhance security for millions.

What You'll Do

• Design and refine backend services using Golang to process and analyze device data, ensuring robustness and scalability.
• Collaborate closely with software engineers, product managers, and other stakeholders to integrate machine learning capabilities seamlessly into our products.
• Develop sophisticated algorithms leveraging high-entropy signals and probabilistic matching to revolutionize device identification.
• Dive into vast datasets to uncover insights, boosting the accuracy and reliability of our systems.
• Apply advanced machine learning models to enhance device recognition and effectively manage uncertainties.
• Maintain the highest standards of privacy and security, aligned with industry best practices and regulations.
• Foster a culture of continuous learning, and document processes clearly to ensure consistency across the team.

What We're Looking For

• 5+ years of experience in software engineering, with a focus on backend development; proficiency in Go or a similar language is essential.
• Bachelor's or Master's in Computer Science, Engineering, or a related discipline.
• Hands-on experience with applied machine learning and data-informed optimization, working with large-scale datasets using tools like PyTorch and Scikit-learn.
• Proficient in SQL for querying and analyzing large datasets.
• Comfortable working with both relational and non-relational databases.
• Proficient in English - from casual chats to formal reports.

Extra Points For

• A strong understanding of cybersecurity principles, especially in device identification and fraud prevention.
• Experience managing cloud infrastructure (AWS, Google Cloud, or Azure).
• Knowledge of containerization tools (Docker, Kubernetes) and CI/CD pipelines.
• Understanding of modern browser APIs and high-entropy data collection techniques.

Compensation:
Base pay range of $330,000 - R440,000+ equity with tremendous upside potential + Attractive benefits

The compensation offered for this role will depend on various factors, including the candidate's location, qualifications, work history, and interview performance, and may differ from the stated range.

Benefits We Offer

• Generous compensation in cash and equity
• Early exercise for all options, including pre-vested
• Work from anywhere: Remote-first Culture
• Flexible paid time off, Year-end break, Self care days off
• Health insurance, dental, and vision coverage for employees and dependents - US and Canada specific
• 4% matching in 401k / RRSP - US and Canada specific
• MacBook Pro delivered to your door
• One-time stipend to set up a home office — desk, chair, screen, etc.
• Monthly meal stipend
• Monthly social meet-up stipend
• Annual health and wellness stipend
• Annual Learning stipend
• Unlimited access to an expert financial advisory

Join a fast-growing company with world-class professionals from around the world. If you are seeking a meaningful career, you found the right place, and we would love to hear from you.

To learn more about how we process your personal information and your rights in regards to your personal information as an applicant and Sardine employee, please visit our
Applicant and Worker Privacy Notice
.

Funções que serão desempenhadas:

• Projetar, construir e implementar sistemas complexos para treinar e executar modelos de aprendizado de máquina com princípios arquitetônicos sólidos;
• Entender os objetivos de negócios e implementar modelos para alcançá-los, juntamente com métricas para acompanhar seu progresso;
• Atuar em parceria com as áreas de negócio, incluindo: Produtos, Sucesso do Cliente e Vendas/Marketing;
• Aplicar as melhores práticas de desenvolvimento, testes e demonstrar excelentes habilidades de software para produzir soluções sustentáveis, escalonáveis e de qualidade.

Requisito
s necessárias:

• Ensino Superior em cursos voltados para Tecnologia;
• Inglês avançado (diferencial);
• Amplo conhecimento em pelo menos uma das principais linguagens de programação (Python, Java ou Scala);
• Conhecimento em Containerização (Docker) ;
• Conhecimento de computação em nuvem (Azure, AWS ou GCP);
• Processamento Distribuído e Paralelo (Spark, Dask, etc.);
• Orquestração e fluxos (Prefect, Airflow, Kubeflow, etc.);
• Pipelines CI/CD (Gitlab, Github, Argo, etc.).

ATENÇÃO
Para essa vaga, o modelo de trabalho é híbrido, sendo presencial três vezes por semana em nosso escritório em Barueri/SP - por isso, o profissional precisa residir em São Paulo ou região de fácil deslocamento.