4.361 Empregos para Machine Learning - Brasil

Estamos em busca de uma pessoa Engenheira de Machine Learning para integrar nossa equipe de Soluções IA e ser responsável por aplicar técnicas de aprendizado de máquina em projetos inovadores, ajudando a construir soluções inteligentes para nossos produtos e clientes.

Se você possui paixão por tecnologia, tem conhecimentos em dados e está em busca de oportunidades para crescer na área, esta é a vaga ideal.

Responsabilidades:

• Projetar, desenvolver e implementar modelos de machine learning para resolver problemas de negócio diversos.
• Automatizar e otimizar processos relacionados ao ciclo de vida de modelos: desde a experimentação, treinamento, deploy até o monitoramento em produção.
• Trabalhar em colaboração com equipes de Ciência de Dados, Engenharia de Dados e Produto, garantindo que os modelos sejam integrados de forma eficiente aos sistemas.
• Garantir a escalabilidade, eficiência e confiabilidade das soluções de machine learning em ambientes de produção.
• Participar da definição de arquiteturas e pipelines de MLOps para automação e governança de modelos.
• Monitorar o desempenho dos modelos e ajustar parâmetros conforme mudanças nos dados e nos objetivos de negócio.
• Documentar soluções, boas práticas e contribuir para a evolução contínua dos processos e padrões técnicos.
• Pesquisar e implementar novas técnicas e ferramentas que impulsionem a inovação em machine learning.
  
  

• Graduação completa ou em andamento em Ciência da Computação, Engenharia, estatística, matemática, ou áreas correlatas.
• Programação em Python ou outras linguagens adequadas para machine learning.
• com bibliotecas e frameworks de machine learning e deep learning (ex.: Scikit-learn, TensorFlow, PyTorch).
• Conhecimento de fundamentos de estatística, aprendizado supervisionado e não supervisionado.
• Experiência com versionamento de código (ex.: Git) e práticas de desenvolvimento de software.
• Noções de deployment e monitoramento de modelos.
  
  

• Experiência prática com MLOps e ferramentas de automação de pipelines (ex.: MLflow, Kubeflow, Airflow).
• Conhecimento em computação em nuvem (AWS, Azure ou GCP), especialmente serviços de IA/ML.
• Experiência com containers e orquestração (ex.: Docker, Kubernetes).
• Implementação de soluções de machine learning em ambientes de produção com requisitos de escalabilidade e segurança.
• Participação em projetos que envolvam modelos de NLP, visão computacional ou sistemas de recomendação.
  
  

• Mentalidade analítica e orientação para a resolução de problemas complexos com pragmatismo.
• Proatividade na busca de soluções e na melhoria contínua de processos e modelos.
• Colaboração ativa com diferentes áreas e habilidades de comunicação clara, tanto para públicos técnicos quanto não técnicos.
• Organização, responsabilidade e atenção aos detalhes na entrega de soluções robustas e seguras.
• Interesse por aprendizado contínuo e atualização em relação às tendências e inovações em machine learning.
  
  

São Paulo, São Paulo, Brazil 3 months ago

São Paulo, São Paulo, Brazil 11 hours ago

São Paulo, São Paulo, Brazil 5 months ago

São Paulo, São Paulo, Brazil 3 months ago

São Paulo, São Paulo, Brazil 2 months ago

Estamos em busca de uma pessoa Engenheira de Machine Learning para integrar nossa equipe de Soluções IA e ser responsável por aplicar técnicas de aprendizado de máquina em projetos inovadores, ajudando a construir soluções inteligentes para nossos produtos e clientes.

Se você possui paixão por tecnologia, tem conhecimentos em dados e está em busca de oportunidades para crescer na área, esta é a vaga ideal.

Responsabilidades:

• Projetar, desenvolver e implementar modelos de machine learning para resolver problemas de negócio diversos.
• Automatizar e otimizar processos relacionados ao ciclo de vida de modelos: desde a experimentação, treinamento, deploy até o monitoramento em produção.
• Trabalhar em colaboração com equipes de Ciência de Dados, Engenharia de Dados e Produto, garantindo que os modelos sejam integrados de forma eficiente aos sistemas.
• Garantir a escalabilidade, eficiência e confiabilidade das soluções de machine learning em ambientes de produção.
• Participar da definição de arquiteturas e pipelines de MLOps para automação e governança de modelos.
• Monitorar o desempenho dos modelos e ajustar parâmetros conforme mudanças nos dados e nos objetivos de negócio.
• Documentar soluções, boas práticas e contribuir para a evolução contínua dos processos e padrões técnicos.
• Pesquisar e implementar novas técnicas e ferramentas que impulsionem a inovação em machine learning.

Requisitos:

• Graduação completa ou em andamento em Ciência da Computação, Engenharia, estatística, matemática, ou áreas correlatas.
• Programação em Python ou outras linguagens adequadas para machine learning.
• com bibliotecas e frameworks de machine learning e deep learning (ex.: Scikit-learn, TensorFlow, PyTorch).
• Conhecimento de fundamentos de estatística, aprendizado supervisionado e não supervisionado.
• Experiência com versionamento de código (ex.: Git) e práticas de desenvolvimento de software.
• Noções de deployment e monitoramento de modelos.

Diferenciais:

• Experiência prática com MLOps e ferramentas de automação de pipelines (ex.: MLflow, Kubeflow, Airflow).
• Conhecimento em computação em nuvem (AWS, Azure ou GCP), especialmente serviços de IA/ML.
• Experiência com containers e orquestração (ex.: Docker, Kubernetes).
• Implementação de soluções de machine learning em ambientes de produção com requisitos de escalabilidade e segurança.
• Participação em projetos que envolvam modelos de NLP, visão computacional ou sistemas de recomendação.

Perfil profissional:

• Mentalidade analítica e orientação para a resolução de problemas complexos com pragmatismo.
• Proatividade na busca de soluções e na melhoria contínua de processos e modelos.
• Colaboração ativa com diferentes áreas e habilidades de comunicação clara, tanto para públicos técnicos quanto não técnicos.
• Organização, responsabilidade e atenção aos detalhes na entrega de soluções robustas e seguras.
• Interesse por aprendizado contínuo e atualização em relação às tendências e inovações em machine learning.

Se você se identifica com essa oportunidade, inscreva-se! Nosso processo valoriza competências, potencial e diversidade de experiências.

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.

Come to one of the biggest IT Services companies in the world! Here you can transform your career!

Why to join TCS? Here at TCS we believe that people make the difference, that's why we live a culture of unlimited learning full of opportunities for improvement and mutual development. The ideal scenario to expand ideas through the right tools, contributing to our success in a collaborative environment.

We are looking for Machine Learning Engineer (MLOps) who wants to learn and transform his career.

In this role you will:

• Proven experience in MLOps
• Hands-on experience with AWS
• Kubernetes for container orchestration
• MLFlow for experiment/model management
• Argus
• Kedro for pipeline orchestration
• Experience with databases (preferably Redshift or other relational database)
• Knowledge of code versioning and CI/CD processes (Jenkins, or similar)
• Strong documentation skills and ability to communicate clearly with both technical and non-technical stakeholders

And much better if you stand out for:

• Agile

Key Responsibilities:

• Deploy, automate, and monitor machine learning models in production environments.
• Develop and maintain data and model pipelines using MLOps tools.
• Provide technical support to the Data Science team, promoting best practices in Machine Learning Engineering and DevOps.
• Evolve and maintain the internal MLOps framework.
• Ensure the security, performance, and scalability of the implemented solutions.

Key Words:

MLOps; AWS, English

<<>>

What do we offer?

• TCS Benefits – Brazil:
• Health insurance
• Dental Plan
• Life insurance
• Transportation vouchers
• Meal/Food Voucher
• Childcare assistance
• Gympass
• TCS Cares – free 0800 that provides psychological assistance (24 hrs/day), legal, social and financial assistance to associates
• Partnership with SESC
• Reimbursement of Certifications
• Free TCS Learning Portal – Online courses and live training
• International experience opportunity
• Discount Partnership with Universities and Language Schools
• Bring Your Buddy – By referring people you become eligible to receive a bonus for each hire
• TCS Gems – Recognition for performance
• Xcelerate – Free Mentoring Career Platform
• Tata Consultancy Services is an equal opportunity employer, our commitment to diversity & inclusion drives our efforts to provide equal opportunity to all candidates who meet our required knowledge & competency needs, irrespective of any socio-economic background, race, color, national origin, religion, sex, gender identity/expression , age, marital status, disability, sexual orientation or any others. We encourage anyone interested to build a career in TCS to participate in our recruitment & selection process.
• At Tata Consultancy Services we promote an inclusive culture, we always work for equity. This applies to Gender, People with Disabilities, LGBTQIA+, Religion, Race, Ethnicity. All our opportunities are based on these principles. We think of different actions of inclusion and social responsibility, in order to build a TCS that respects each person. Our motto is Inclusion without exception.

At TATA Consultancy Services we promote an inclusive culture, we always work for equity. This applies to Gender, People with Disabilities, LGBTQIA+, Religion, Race, Ethnicity. All our opportunities are based on these principles. We think of different actions of inclusion and social responsibility, in order to build a TCS that respects individuality. Come to be a TCSer!

#Buildingonbelief

• RGS -

Join to apply for the Machine Learning Expert role at Accenture Argentina

Los Machine Learning Engineers diseñan, desarrollan e implementan sistemas de aprendizaje automático para resolver problemas del mundo real. Trabajan con datos para crear modelos, realizar análisis estadísticos y entrenar y reentrenar sistemas para optimizar el rendimiento.

• Diseñar y desarrollar sistemas de aprendizaje automático.
• Trabajar con datos para limpiarlos, prepararlos y analizarlos.
• Implementar algoritmos de aprendizaje automático y entrenar modelos.
• Evaluar el rendimiento del modelo y realizar los ajustes necesarios.
• Implementar sistemas de aprendizaje automático en producción y monitorear su desempeño.
• Colaborar con otros ingenieros, científicos de datos y gerentes de productos.
• Manténgase actualizado sobre los últimos avances en aprendizaje automático

• Ayudar con la recopilación, limpieza y preprocesamiento de datos. Esto implica recopilar datos de una variedad de fuentes, limpiarlos para eliminar errores e inconsistencias y prepararlos en un formato que pueda usarse para modelos de aprendizaje automático.
• Desarrollar y entrenar modelos. Esto implica seleccionar el algoritmo de aprendizaje automático apropiado para el problema en cuestión, entrenar el modelo con los datos preparados y evaluar el rendimiento del modelo.
• Implementar modelos en producción. Esto implica poner el modelo entrenado a disposición de los usuarios para que pueda hacer predicciones sobre nuevos datos.
• Monitorear y mantener modelos de aprendizaje automático. Esto implica monitorear el desempeño de los modelos implementados y realizar los ajustes necesarios para garantizar que continúen funcionando bien.
• Colaborar con otros ingenieros y científicos de datos. Suelen trabajar en equipos multifuncionales con otros ingenieros y científicos de datos para desarrollar e implementar soluciones.
• A su vez, deberá coordinar la ejecución de actividades dentro de un equipo reducido, asegurarse que las mismas se ejecuten en tiempo y forma. En caso de haber demoras deberá sentirse cómodo para informar los retrasos y generar un plan de contingencias.
• Trabajará con expertos de distintos tipos optimización, ML, simulación, UX.
• Deberá interpretar los requerimientos del cliente, para así poder estimar tiempo y esfuerzo del desarrollo de las tareas. Esta estimación deberá hacerse teniendo en cuenta los datos disponibles, la implicancia del requerimiento a desarrollar sobre el modelo existente y posible efecto sobre el output del modelo.

• Pedidos Ya
• Prepaga Swiss Medical sin costo para vos y tu grupo familiar primario
• Reintegro de Conectividad
• Gimnasio 100% Bonificado
• Vacaciones Flex
• Jornada Flex
• Certificaciones bonificadas
• Día de cumpleaños libre
• Bonos
• Accenture Days
• Paquete de beneficios flexibles
• Licencias de Paternidad & Maternidad Extendida
• Ayuda Económica para Guardería y muchos más

EN ACCENTURE, LA IGUALDAD IMPULSA LA INNOVACIÓN. ¿Sabías que Accenture fue elegida la compañía más diversa e inclusiva del mundo? Creemos que la fuerza laboral del futuro es una fuerza igualitaria para todos. Todas las decisiones referidas al proceso de selección de empleo se tomarán sin hacer distinción, exclusión o preferencia alguna basada en motivos de raza, color, género, orientación sexual, discapacidad, edad, religión, opinión política o sindical, nacionalidad u origen socioeconómico ni ninguna otra prevista en la legislación vigente, que tengan por efecto anular o alterar la igualdad de oportunidades o de trato entre los candidatos.

• Entry level

• Full-time

• Engineering and Information Technology

• Business Consulting and Services

Referrals increase your chances of interviewing at Accenture Argentina by 2x

We’ve removed extraneous prompts to focus on the role content.

Join to apply for the ESTAGIÁRIO MACHINE LEARNING role at Concessionária Nova Rota do Oeste .

O estagiário tem como missão principal apoiar a equipe de desenvolvimento do projeto RDT para implementação dos algoritmos desenvolvidos durante a pesquisa, manutenção da infraestrutura computacional e produção de documentação.

• Apoiar no desenvolvimento de tecnologia que realizará o processamento automático por meio de Inteligência Artificial dos levantamentos registrados com câmeras 360º e Line-Scan.

• Cursando Ciência da Computação
• Disponibilidade para trabalhar em período de 4 horas (08:00 às 12:00)
• Inglês intermediário

• Salário compatível com o mercado
• Plano de Saúde
• Vale Alimentação
• Auxílio academia
• Vale Transporte

• Internship

• Internship

• Other

• Civil Engineering

Machine Learning Engineer at TRACTIAN. We’re hiring a Mid-Level Machine Learning Engineer to bridge the gap between data science and production systems. You’ll own end-to-end deployment of machine learning models, work with real-time sensor data, and build reliable services that power diagnostics for industrial equipment. This is a hands-on role with real impact, ideal for engineers who want to grow their systems design and ML Ops skills.

The Data Science team at TRACTIAN focuses on extracting valuable insights from vast amounts of industrial data. Using advanced statistical methods, algorithms, and data visualization techniques, this team transforms raw data into actionable intelligence that drives decision-making across engineering, product development, and operational strategies. The team constantly works on optimizing prediction models, identifying trends, and providing data-driven solutions that directly enhance the company’s operational efficiency and the quality of its products.

We’re hiring a Mid-Level Machine Learning Engineer to bridge the gap between data science and production systems. You’ll own end-to-end deployment of machine learning models, work with real-time sensor data, and build reliable services that power diagnostics for industrial equipment. This is a hands-on role with real impact, ideal for engineers who want to grow their systems design and ML Ops skills.

• Deploy and maintain ML models from the data science team
• Design and implement APIs and real-time inference services
• Work with large-scale time-series datasets from vibration and sensor systems
• Improve the performance and reliability of model serving pipelines
• Monitor system health and implement logging, alerting, and fallback mechanisms
• Contribute to architectural decisions and collaborate across teams

• 2–4 years of experience in software or machine learning engineering
• Bachelor’s degree in Computer Science, Engineering, or related technical field
• Solid background in math, statistics, and machine learning concepts
• Strong Python skills and experience with ML libraries like scikit-learn or PyTorch
• Experience deploying models in production environments
• Familiarity with event-driven platforms and message queues (e.g., Kafka, Redis Streams)
• Comfort working with streaming or time-series data

• Experience with containerization (Docker) and cloud deployment
• Exposure to real-time or low-latency systems
• Interest in optimization of inference latency and resource usage

• Programming: Python, Golang
• ML Libraries: scikit-learn, PyTorch, TensorFlow
• Backend: FastAPI, Flask
• Infrastructure: Kafka, Redis, PostgreSQL, Docker
• ML Ops: Model serving, monitoring, CI/CD pipelines

• Mid-Senior level

• Full-time

• Engineering and Information Technology

• Software Development

A Aprix é uma empresa que desenvolve soluções Saas voltadas para precificação. Nossa missão é desenvolver soluções de data science que auxiliem agentes de diferentes portes e segmentos a solucionar problemas na busca por maior eficiência.

A missão de uma pessoa na trilha de MLE é participar ativamente do desenvolvimento e aprimoramento do produto de precificação da Aprix para grandes empresas. As atividades envolvem tratamento, limpeza e automação de processos de dados, realização de análises estatísticas, criação de modelos preditivos e otimização de preços. Nessa oportunidade, você terá contato com os nossos modelos de precificação em Python, com bases de dados SQL, Git e Cloud, além de interações frequentes com clientes, outros desenvolvedores e Product Owners, auxiliando na evolução do produto.

• Cursos: Engenharias, Ciências da Computação ou correlatas.

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.

• 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

• 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.

Mid-Senior level

Full-time

• Business Consulting and Services