Principal Machine Learning Engineer
Core
Designing and deploying advanced AI/ML systems with a focus on Reinforcement Learning (RL) and decision intelligence for enterprise platforms.
Role type
Principal-level AIML Engineer (Reinforcement Learning & Decision Intelligence)
Builds
Scalable AI solutions, production-grade RL models, and agent-based systems for real-world decision-making.
Domain
Biotechnology / Enterprise AI / Reinforcement Learning
Deliverable
production ML models
Required skills
Reinforcement Learning (Deep RL, Policy Optimization, RLHF), Python, MLOps (MLflow, Kubeflow, SageMaker), Distributed Systems & Cloud (AWS/Azure/GCP), Model deployment and lifecycle management, ML/DL algorithms and optimization techniques
Preferred skills
Multi-agent systems / agentic AI frameworks, LLMs, RAG, or Generative AI systems, Simulation environments (Gym, RLlib), Optimization, control systems, or operations research
Technologies
Python, MLflow, Kubeflow, SageMaker, AWS, Azure, GCP, Gym, RLlib
Responsibilities
Design and develop Reinforcement Learning models for real-world decision-making; Build and deploy scalable ML pipelines and production AI systems; Architect end-to-end AI systems integrating RL with GenAI, LLMs, or agent-based frameworks; Lead development of agent-based / multi-agent AI systems for planning, reasoning, and automation; Translate research concepts into production-grade, reliable ML systems; Evaluate new AI techniques and drive adoption; Mentor engineers and provide technical leadership and architectural guidance
Seniority
Principal, technical leadership & hands-on IC
