ML Engineer / Data Scientist

Job Title: Data Science / ML Engineer
Location: Remote – Latin America - 6 AM – 2 PM Pacific Time
Type of Contract: Full-Time | Contractor
Salary Range: $3,000 to $5,500 USD
Language Requirements: Professional English

We are seeking a skilled ML Engineer / Data Scientist with strong experience in reinforcement learning environments and AI systems to join our growing team. You will play a key role in designing scalable evaluation frameworks and shaping the behavior of advanced AI models. Your work will directly impact the performance, reliability, and alignment of cutting-edge AI agents.

Key Responsibilities

• Design and implement reinforcement learning (RL) environments for large-scale agent evaluation and experimentation
• Build task generation pipelines, dynamic datasets, and controlled simulation environments with varying complexity
• Develop reward models and verification systems to automatically evaluate model outputs and reasoning paths
• Collaborate with infrastructure teams to ensure systems are scalable, reproducible, and fully instrumented for telemetry
• Design APIs and orchestration frameworks to manage agent lifecycle across environments
• Optimize performance, logging systems, and reward consistency in distributed environments
• Contribute to continuous improvements in evaluation methodologies and AI behavior alignment

Must-Have Qualifications

• 5+ years of experience in Python software engineering
• 3+ years of experience in Data Science, Machine Learning, or Environment Engineering roles
• Strong practical experience working with AI systems, including prompt engineering
• Hands-on experience with AI frameworks such as LangChain, LangGraph, or MCP servers
• Solid understanding of reinforcement learning concepts, including reward modeling, environment dynamics, and agent interaction loops
• Experience working with metrics, instrumentation, and data pipelines for ML or RL systems
• Ability to work 6 AM – 2 PM Pacific Time

Preferred Qualifications

• Experience with tools such as Codex or Claude Code
• Background in integrating AI systems into production environments
• Familiarity with evaluation frameworks for large language models
• Strong self-management and ability to plan and execute work independently