Data Science/ML Engineer (Remote, LATAM)

Why Blue Coding?

At Blue Coding, we specialize in hiring excellent developers and amazing people from all over Latin America and other parts of the world. For the past 11 years, we’ve helped cutting-edge companies in the United States and Canada build great development teams and develop great products. Large multinationals, digital agencies, Saas providers, and software consulting firms are just a few of our clients. Our team of over 150 engineers, project managers, QA, UX/UI designers, and many more is distributed in more than 10 countries across the Americas. We are a fully remote company working with a wide array of technologies, and we have expertise in every stage of the software development process.

Our team is highly connected, united, and culturally diverse, and our collaborators are involved in many initiatives around the world, from wildlife preservation to volunteering at local charities. We stand for honesty, fairness, respect, efficiency, hard work, and cooperation.

This position is open exclusively to candidates based in LATAM countries.

What are we looking for?

In this opportunity, we are looking for a Data Science/ML Engineer to work with one of our foreign clients, a company that's a leading provider of AI evaluation and optimization solutions, and to detect performance issues in large language models.

If you are fully fluent in English, proactive, communicate well, like to solve problems, and have a strong attention to detail, this role might be a great fit for you! Our jobs are fully remote, and you will be integrated directly into the client’s team, gaining valuable experience and forming meaningful connections.

What’s unique about this job?

• In this role, you’ll help develop advanced reinforcement learning (RL) environments and scalable evaluation systems that guide and shape the behavior of cutting-edge AI models
  
  
  
  

Here are some of the exciting day-to-day challenges you will face in this role:

• Design and implement RL environments that support large-scale agent evaluation and reinforcement learning experiments
• Build task generation pipelines, dynamic datasets, and scripted environments with controlled complexity and stochasticity
• Develop verifiers and reward models to score trajectories and evaluate model reasoning automatically

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• Collaborate with infrastructure and systems engineers to ensure environments are scalable, reproducible, and instrumented for detailed telemetry
• Design APIs and orchestration frameworks for running, resetting, and evaluating agents across environments
• Optimize environment performance, logging, and reward reproducibility across distributed setups
  
  
  
  

You will shine if you have:

• Strong experience in Python software engineering
• Minimum 3 years in a Data Scientist, Machine Learning/Environment Engineering position or similar
• Ability to work from 6 AM - 2 PM Pacific time
• Bachelor's degree in Computer Science or related field
• Practical knowledge of AI frameworks (Langchain, Langraph, mcp-server )
• Extensive practical experience in working with AI, including prompt engineering and vibe coding
  
  
  
  

It doesn’t hurt if you also have:

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• Knowledge of Codex or Claude Code
• Experience in integrating AI with a system would be an advantage
• Understanding of Reinforced Learning concepts - reward modeling, environment dynamics, verifiability, evaluation, and agent interaction loops
• Familiarity with instrumentation, metrics, and data pipelines for RL evaluation
• Expertise in planning your own work
  
  
  
  

Here are some of the perks we offer you:

• Salary in USD
• 100% Remote
  
  
  
  

Ready to learn more? Apply below!

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.