Staff ML Engineer: RL & Scalable AI Systems Leader

People In AI; San Francisco (CA); Hybrid; USD 265,000 - 280,000; Full time

Benefits offered by this job

Hybrid work model

Equity

Job summary

People In AI in San Francisco is seeking a Staff-level Machine Learning Engineer to join the rapidly growing ML team. You will work on reinforcement learning, model post-training, and evaluation, bridging research and production systems.

The role emphasizes hands-on engineering, technical leadership, and scalable infrastructure. You will design architectures, run large-scale experiments, and guide a small team through ambiguous problems while shipping robust ML workflows.

Qualifications

• Hands-on ML engineering experience beyond model deployment or API integration.
• Experience with model fine-tuning or post-training workflows.
• Experience with reinforcement learning, evaluation, and training environments.
• Strong ability to lead technically without formal authority.
• Comfort in ambiguous, rapidly changing environments.
• Excellent Python and production software fundamentals.

Responsibilities

• Design and build reinforcement learning environments for agentic tasks.
• Develop task definitions, tool interfaces, state management, reward structures, and evaluation logic.
• Build systems capable of running large numbers of agent trajectories and experiments in parallel.
• Develop verifiers, graders, rubrics, and other evaluation methods for open-ended model behavior.
• Build fine-tuning and post-training pipelines spanning supervised fine-tuning and reinforcement learning.
• Run ML experiments and diagnose model behavior, training performance, reward quality, and data quality.
• Build scalable evaluation systems to measure model and agent performance.
• Develop production-grade ML infrastructure, including orchestration, reliability, fault tolerance, and experiment management.
• Translate ambiguous technical problems into clear architectures and execution plans.
• Provide technical leadership to other engineers while remaining hands-on.
• Use modern AI development tools while maintaining engineering judgment around the systems they produce.

Skills

Hands-on ML Engineering

Python

Distributed Systems

Production-grade Software Engineering

Technical Leadership

Model Evaluation & Post-Training

Experimentation & R&D

Job description

People In AI in San Francisco is seeking a Staff-level Machine Learning Engineer to join the rapidly growing ML team. You will work on reinforcement learning, model post-training, and evaluation, bridging research and production systems.

The role emphasizes hands-on engineering, technical leadership, and scalable infrastructure. You will design architectures, run large-scale experiments, and guide a small team through ambiguous problems while shipping robust ML workflows.