Machine Learning Engineer

What You'll Work On

At Reinforce Labs, we build the red teaming, agent evaluations, RL environments, and safety infrastructure that make frontier AI reliable in the real world.

You'll move between applied research, client-facing engineering, and infrastructure — translating cutting-edge papers into systems that ship, and shipping work that ends up in papers. 

Key responsibilities:

• Building RL environments for training and evaluation
• Developing agent and task evaluation systems that measure frontier model capabilities in realistic, high-stakes settings
• Mapping customer workflows and building AI probes that surface edge-case failures
• Training specialized classifiers that detect subtle risks, violations, and anomalies
• Fine-tuning generative models that simulate rare or high-risk scenarios
• Collaborating with university partners on joint research and co-authored publications

Must-Have

• Ability to turn research papers into working systems
• Hands-on experience post-training and deploying LLM
• Building complex AI agent applications
• Proficiency in Python
• LLM and agentic framework experience
• Advanced degree in CS or related field

Nice-to-Have

• Experience building RL environments or training agents (PPO, GRPO, DPO, RLHF, etc.)
• Experience designing evaluations for LLMs or agentic systems
• Research publications or contributions to open-source AI/ML projects
• Early-stage startup experience
• Customer-facing AI technical experience