317 Empregos para Machine learning - Jundiaí

Base pay range

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.

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 DL 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.

• 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 built 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.

• 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.

• 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.

• 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.

Prazer, somos a Huna!
- Deeptech brasileira construindo o futuro do diagnóstico precoce de câncer para 99% da humanidade usando inteligência artificial e exames de rotina!
:) Construímos tecnologias robustas, éticas e responsáveis para ampliar o acesso à saúde… e que bom que você quer fazer parte dessa trajetória com a gente!
:) Estamos contratando para vaga de PESSOA ENGENHEIRA DE MACHINE LEARNING (MLOps) (Pleno) - até dia 21 de Março!
Esta é uma vaga full-time e remote-first , com preferência para candidatos baseados em São Paulo (Capital e RM) e Rio de Janeiro.
É importante ter disponibilidade para viagens ocasionais (e alguns eventos nas sedes da empresa em ambas cidades).

1. Pesquisar e implementar algoritmos e ferramentas de Machine Learning apropriados para resolver problemas específicos na área da saúde, como diagnóstico auxiliado por IA, previsão de riscos, personalização de tratamentos e análise de imagens médicas;
2. Desenvolver aplicações de Machine Learning de acordo com os requisitos, utilizando linguagens de programação como Python e bibliotecas como TensorFlow, PyTorch e Scikit-learn;
3. Estudar e transformar protótipos de ciência de dados em soluções escaláveis e robustas;
4. Ampliar bibliotecas e estruturas de ML existentes para atender às necessidades específicas das aplicações;
5. Selecionar conjuntos de dados apropriados para treinar os modelos de Machine Learning, realizando a limpeza, a transformação e a preparação dos dados;
6. Escolher métodos de representação de dados eficazes para otimizar o desempenho dos modelos;
7. Realizar análises estatísticas e ajustes finos nos modelos, utilizando resultados de testes para melhorar a acurácia e a eficiência;
8. Treinar e retreinar os sistemas de Machine Learning quando necessário, utilizando técnicas de aprendizado supervisionado, não supervisionado e por reforço;
9. Otimizar os modelos para garantir o desempenho, a escalabilidade e a eficiência em ambientes de produção.

1. Formação em Ciência da Computação, Engenharia, Estatística ou áreas correlatas.
2. Experiência mínima de 2 (dois) anos na função.
3. Experiência com linguagens de programação como Python e bibliotecas de Machine Learning como TensorFlow, PyTorch e Scikit-learn.
4. Inglês avançado.
5. Conhecimento de algoritmos de Machine Learning, como regressão, classificação, clustering e deep learning.
6. Habilidade em processar e analisar grandes conjuntos de dados.
7. Familiaridade com ferramentas de controle de versão, como Git.
8. Disponibilidade para viagens eventuais.

1. Pós-Graduação (Mestrado ou Doutorado - completa ou em andamento) em áreas correlatas.
2. Conhecimento de processamento de linguagem natural (PNL) ou visão computacional.
3. Familiaridade com plataformas de cloud computing, especialmente GCP, AWS ou Azure.
4. Experiência prévia (acadêmica ou profissional) com manipulação de dados clínicos/médicos e/ou vivência no setor de saúde.

1. Remuneração compatível com o mercado.
2. Benefício flexível (Caju).
3. Benefício de saúde (Gympass).
4. Benefício de educação.
5. Possibilidade de participar de programa de S.O.P.
6. Rotina remote-first (remoto preferencial).
7. Short-Fridays.
8. Flexibilidade de horários na rotina.
9. Day-off de aniversário.
10. Emendas de feriados nacionais.

> Se você acha que essa vaga é a sua cara, inscreva-se na vaga diretamente pelo ou por email ***.
> Se conhece alguém que se encaixa no perfil, compartilhe!
LEMBRETE: O prazo vai até dia 21 de Março.
Somente candidatos selecionados receberão feedback para as próximas etapas.
:)

Employment type:

B2B

Operating mode:

Remote

Location:

We help companies gain a competitive edge by delivering customized AI solutions. Our mission is to empower our clients to unlock the full potential of AI.

We are specialized in key technologies such as LLM & RAG, MLOps, Edge Solutions, Computer Vision, and Natural Language Processing.

Our team of 120 world-class AI experts has worked on 200+ commercial and R&D projects with companies such as Unstructured, Google, Brainly, DocPlanner, B-Yond, Zebra Technologies, Hexagon, and many more.

• Team Strength – sharing and exchanging knowledge is key to our daily work
• Accountability – we take responsibility for the tasks entrusted to us so that ultimately the client receives the best possible quality
• Balance – we value work-life balance
• Commitment – we want you to be fully part of the team
• Openness – we don’t want you to be locked into one solution, we want to look for alternatives, explore new possibilities

Join our dynamic team as a Machine Learning Engineer and embark on a journey of innovation at the intersection of data science and cloud computing. We are seeking a talented individual who is passionate about leveraging cutting-edge technologies to drive business insights and solutions. If you’re excited about pushing the boundaries of what’s possible with GenAI, we invite you to be part of our team of experts!

• Collaborate with data scientists and software engineers to integrate machine learning solutions into cloud-based applications.
• Continuously optimize and improve AI algorithms for performance and accuracy in a cloud environment.
• Automate and optimize model deployment following MLOps best practices.
• Engage in the development of cutting-edge Kubernetes-driven infrastructure.
• Work on system reliability and backend stability, always looking for details to be improved.
• Share knowledge through talks and workshops (internal and external).

• Bachelor’s or advanced degree in Computer Science or Engineering.
• Proven experience (3+ years) in software engineering, including experience with Python, Bash, Git, as well as Cloud services, and Linux.
• Proven experience (1+ years) in working with cloud (AWS/Azure preferred).
• Good understanding of system architecture (microservices, monoliths, REST API, DNS, caching).
• Familiarity with Docker, Kubernetes, and cloud platforms for ML deployment.
• Strong Python skills and familiarity with other object-oriented languages.
• Very effective communication skills, both written and verbal.
• Ability to solve problems and communicate complex ideas effectively.

• Basic understanding of machine learning algorithms.
• Keen interest for Generative AI and Large Language Models (LLMs).
• Previous startup experience.

• Opportunity to work on cutting-edge AI projects with a diverse range of clients and industries, driving solutions from development to production.
• Collaborative and supportive work environment, where you can grow and learn from a team of talented professionals.
• An opportunity to participate in conferences and workshops.
• An opportunity to participate in Tech Talks (internal training and seminar sessions).
• Remote work options and travel to European headquarters available.

• Medical package.
• Multisport cards.
• Lunch provided.
• Kitchens stocked with fruit and veggies twice a week.
• Monthly integration budget.
• Company library (online and offline).
• Fun room.

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.

Our MLOps offering focuses on building and maintaining the robust infrastructure essential for our cutting-edge AI solutions. As a ML Ops Engineer at Lateral, you will be crucial in ensuring the smooth operation and scalability of our AI initiatives through a variety of critical tasks:

• Infrastructure Management: You will be responsible for defining and proposing an infrastructure management stack that drives business objectives.

• Troubleshooting and Optimization: You will help identify and mitigate AI infrastructure issues and implement features to improve model training speed on specific hardware.

• Platform Evaluation and Implementation: You will evaluate and implement new AI training and development platforms.

• Automation and Orchestration: Your responsibilities will include automating model training and checkpointing using MLOps tools, and maintaining containerization tools (Docker, Singularity) for reproducibility.

• Deployment and Lifecycle Management: You will facilitate the transfer and replication of models from R&D to production environments, manage the model lifecycle, implement model tracking, and ensure infrastructure remains compatible with evolving training packages (e.g., CUDA, PyTorch, drivers). This includes proactively updating packages and resolving compatibility issues to avoid regressions in training workflows.

We’re seeking pragmatic infrastructure engineers who love solving deep tech problems and enabling great ML work. You’ll thrive in this role if you bring:

• 5+ years of hands-on experience with ML Ops tools such as SLURM, MLflow, Kubeflow, SageMaker, or Vertex AI.

• Experience managing Kubernetes clusters and distributed training workloads at scale.

• Proficiency with containerization (Docker, Singularity) and reproducible ML environments.

• Familiarity with popular deep learning frameworks (PyTorch, TensorFlow) and how they operate at infra level.

• Solid understanding of model lifecycle best practices (training, validation, deployment, tracking).

• Strong scripting and automation skills in Python, Bash, or similar.

• Comfort working closely with ML researchers to translate needs into scalable, production-grade systems.

• A proactive mindset: you're excited to take ownership of infra problems others avoid.

Bonus points for:

• Experience with multi-node, hardware-optimized training setups (e.g. GPU clusters, TPUs).

• Contributions to internal tools or open-source projects in the ML Infra space.

• Prior experience helping bring ML systems through regulatory, safety, or quality review stages.

• 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.

Overview

WHO ARE WE? Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. As The Discovery and Conversion Company, our mission is to connect consumers with the world’s leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.

WHY JOIN US? At Launch Potato, you’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers.

You will build systems that drive millions in revenue through intelligent personalization and optimization. You'll develop and deploy models that understand user preferences, optimize content discovery, and personalize experiences at scale. This is a hands-on role where you'll see direct impact on business metrics daily.

• Build and deploy ML models serving 100M+ predictions daily
• Develop ranking algorithms that balance relevance, diversity, and revenue
• Implement real-time personalization features with <50ms latency requirements
• Run A/B tests and analyze model performance against business KPIs
• Optimize models for production (latency, throughput, cost)
• Collaborate with product teams to identify new personalization opportunities

• 5+ years building production ML systems
• Strong experience with ranking algorithms (collaborative filtering, deep learning, learning-to-rank)
• Proficiency in Python and ML frameworks (TensorFlow/PyTorch)
• Experience with distributed computing (Spark, Ray)
• Track record of shipping models that improve business metrics
• BS/MS in Computer Science, Machine Learning, or related field

Apply now!

Since day one, we've been committed to having a diverse, inclusive team and culture. We are proud to be an Equal Employment Opportunity company. We value diversity, equity, and inclusion. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

• Mid-Senior level

• Full-time

• Engineering and Information Technology

• Advertising Services

Referrals increase your chances of interviewing at Launch Potato by 2x.

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2 days ago Be among the first 25 applicants

N-iX is looking for a Senior Machine Learning Engineer to join a high-impact initiative in the life sciences domain. You will be responsible for designing, developing, and deploying machine learning models at scale within the Palantir Foundry ecosystem, enabling data-driven decision-making across R&D, commercial, and real-world evidence use cases.

You will collaborate closely with data scientists, MLOps engineers, and data engineers to build robust, production-grade ML workflows—from data preparation and feature engineering to model training, evaluation, deployment, and monitoring.

Key Responsibilities

• Design and implement scalable ML models for use in predictive analytics, forecasting, and classification tasks within the pharmaceutical domain.
• Work with Palantir Foundry to build end-to-end ML pipelines, including custom Python code, Foundry Functions, and Ontology-aware feature generation.
• Collaborate with Data Engineers to ensure high-quality, model-ready data flows from ingestion to inference.
• Operationalize models using industry best practices for versioning, reproducibility, and monitoring (e.g., via MLflow or native Foundry tools).
• Contribute to MLOps automation, including CI/CD for ML, drift detection, retraining pipelines, and evaluation dashboards.
• Partner with business stakeholders and domain experts to translate scientific or commercial hypotheses into model-based solutions.
• Apply rigorous experimentation and statistical validation to ensure models are explainable, generalizable, and regulatory-compliant.
• Stay informed on the latest developments in ML/AI and proactively introduce innovative techniques and frameworks.
  
  

• 5+ years of experience in machine learning or applied data science, ideally in a production or enterprise setting.
• Strong programming skills in Python, with deep experience in machine learning libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Experience designing and deploying ML workflows at scale, preferably with experience in Foundry, KubeFlow, SageMaker, or similar platforms.
• Familiarity with feature engineering, data imputation, sampling strategies, and evaluation techniques
• Hands-on experience with model deployment and monitoring, including logging metrics, detecting drift, and managing model lifecycles.
• Comfort working with structured and unstructured data: tabular, time series, text, etc.
• Solid understanding of data security, privacy, and compliance, particularly in pharma or regulated domains.
• Strong communication and stakeholder engagement skills; capable of explaining complex models in simple terms.
• Upper-Intermediate or Advanced level of English is required.
  
  

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits
• not applicable for freelancers

• Seniority level Not Applicable

• Employment type Full-time

• Industries Real Estate, Financial Services, and Capital Markets

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Get notified about new Senior Machine Learning Engineer jobs in Brazil .

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Join to apply for the Senior Machine Learning Engineer role at Launch Potato

5 days ago Be among the first 25 applicants

Join to apply for the Senior Machine Learning Engineer role at Launch Potato

WHO ARE WE?

Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState.

As The Discovery and Conversion Company, our mission is to connect consumers with the world’s leading brands through data-driven content and technology.

Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.

WHY JOIN US?

At Launch Potato, you’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers.

YOUR ROLE

You will build systems that drive millions in revenue through intelligent personalization and optimization. You'll develop and deploy models that understand user preferences, optimize content discovery, and personalize experiences at scale. This is a hands-on role where you'll see direct impact on business metrics daily.

What You'll Do

Overview

Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. As The Discovery and Conversion Company, our mission is to connect consumers with the world’s leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.

You will build systems that drive millions in revenue through intelligent personalization and optimization. You'll develop and deploy models that understand user preferences, optimize content discovery, and personalize experiences at scale. This is a hands-on role where you'll see direct impact on business metrics daily.

• Build and deploy ML models serving 100M+ predictions daily
• Develop ranking algorithms that balance relevance, diversity, and revenue
• Implement real-time personalization features with <50ms latency requirements
• Run A/B tests and analyze model performance against business KPIs
• Optimize models for production (latency, throughput, cost)
• Collaborate with product teams to identify new personalization opportunities

• 5+ years building production ML systems
• Strong experience with ranking algorithms (collaborative filtering, deep learning, learning-to-rank)
• Proficiency in Python and ML frameworks (TensorFlow/PyTorch)
• Experience with distributed computing (Spark, Ray)
• Track record of shipping models that improve business metrics
• BS/MS in Computer Science, Machine Learning, or related field

Want to accelerate your career? Apply now!

Since day one, we've been committed to having a diverse, inclusive team and culture. We are proud to be an Equal Employment Opportunity company. We value diversity, equity, and inclusion. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

• Mid-Senior level

• Full-time

• Engineering and Information Technology

• Advertising Services

Overview

Join to apply for the Senior Machine Learning Engineer role at Launch Potato . Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. As The Discovery and Conversion Company, our mission is to connect consumers with the world’s leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.

WHY JOIN US? At Launch Potato, you’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers.

You will build systems that drive millions in revenue through intelligent personalization and optimization. You'll develop and deploy models that understand user preferences, optimize content discovery, and personalize experiences at scale. This is a hands-on role where you'll see direct impact on business metrics daily.

• Build and deploy ML models serving 100M+ predictions daily
• Develop ranking algorithms that balance relevance, diversity, and revenue
• Implement real-time personalization features with <50ms latency requirements
• Run A/B tests and analyze model performance against business KPIs
• Optimize models for production (latency, throughput, cost)
• Collaborate with product teams to identify new personalization opportunities

• 5+ years building production ML systems
• Strong experience with ranking algorithms (collaborative filtering, deep learning, learning-to-rank)
• Proficiency in Python and ML frameworks (TensorFlow/PyTorch)
• Experience with distributed computing (Spark, Ray)
• Track record of shipping models that improve business metrics
• BS/MS in Computer Science, Machine Learning, or related field

Want to accelerate your career? Apply now!

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• Mid-Senior level

• Full-time

• Engineering and Information Technology

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