ML Engineer
Amigo
Software Engineering, Data Science
Posted on May 13, 2025
ML Engineer
To apply, send us your resume and anything else you'd like to careers@amigo.ai
About Amigo
We're helping enterprises build autonomous agents that reliably deliver specialized, complex services—healthcare, legal, and education—with practical precision and human-like judgment. Our mission is to build safe, reliable AI agents that organizations can genuinely depend on. We believe superhuman level agents will become an integral part of our economy over the next decade, and we've developed our own agent architecture to solve the fundamental trust problem in AI. Learn more here.
Role
As an ML Engineer at Amigo, you'll implement and scale our reinforcement learning systems as we transition from a scaffolded architecture to advanced RL approaches. Reporting to the ML Infrastructure Lead, you'll build efficient pipelines for agent training, evaluation, and continuous improvement within our evolutionary chambers. You'll transform research prototypes into production-ready systems that operate reliably at enterprise scale, enabling our agents to evolve toward superhuman performance. This role is critical for our 6-12 month strategic goal of implementing recursion algorithms for agent-building-agents and advancing our reinforcement learning capabilities.
Responsibilities
Implement and optimize reinforcement learning pipelines based on our evolutionary chamber framework
Build infrastructure for simulating thousands of agent scenarios with perfect reproducibility
Develop systems for reward modeling, continuous training loops, and automated evaluation
Create efficient implementations of research prototypes that scale to production requirements
Implement metrics collection and model evaluation frameworks that enable transparent performance measurement
Build tools for automated agent validation that ensure safety and reliability constraints are maintained
Implement model versioning, experiment tracking, and reproducible training workflows
Create infrastructure for simulator, judge, and agent components within our three-layer evolution approach
Develop optimization systems that ensure efficient resource utilization as we scale to 100x volume
Build model serving infrastructure that maintains reliability under enterprise workloads
Implement the technical components of our Trust Center Framework (agi.work) for validated performance
Collaborate with Researchers to understand requirements and translate research into production systems
Qualifications
3+ years of experience in machine learning engineering, particularly with reinforcement learning or LLM systems
Strong programming skills with expertise in Python and ML frameworks (PyTorch, TensorFlow, etc.)
Experience building and optimizing training pipelines for complex ML models
Background implementing reinforcement learning, RLHF, or similar approaches in production
Experience with distributed computing and parallel processing for ML workloads
Familiarity with experiment tracking, model versioning, and reproducible ML practices
Understanding of ML system requirements for reliability and performance at scale
Experience translating research prototypes into production-ready systems
Background working with simulation frameworks or synthetic data generation
Strong problem-solving skills with attention to resource optimization
Excellent collaboration abilities for working with both researchers and engineers
Location: NYC (Onsite)
To apply, send us your resume and anything else you'd like to careers@amigo.ai