Research Engineer, RL Env

The role

You will build reinforcement learning environments to help researchers train models and understand their capabilities. You will translate real tasks into computational problems and implement environments for model training.

What you will do

• Define tasks, observations, actions and state transitions.
• Implement reset behavior, termination conditions and measurable outcomes.
• Translate task objectives into feedback and evaluation criteria.
• Test whether agents can exploit scoring rules.
• Implement baseline agents, train and compare policies.
• Design controlled experiments to isolate effects of data, methods and environment changes.
• Separate training and held-out tasks, check for leakage, version experiments and repeat runs.
• Report uncertainty and performance across conditions.
• Inspect trajectories and learning behavior to distinguish policy limitations from data, reward or environment problems.
• Work with domain experts and engineers to turn research prototypes into reusable environments and tools.

Required qualifications

• RL environment expertise in formulating problems, constructing environments, training agents and assessing results.
• Strong programming and software debugging skills.
• Sound experimental design and statistical reasoning.
• Ability to reason about environment dynamics, reward design and agent behavior.
• Independent research judgment and clear communication.

Nice to have

• Experience building interactive environments, simulators or benchmarks used by other researchers.
• Work on agent evaluation, reward design, imitation learning or learning from real-world data.
• Research artifacts with reproducible experiments, useful baselines and evidence of investigating failures.

About the company

Mecka AI is building the data infrastructure layer for robotics and embodied AI. They design and operate global systems for data capture, data labeling, and hardware-enabled workflows.