Research Engineer, RL Env

AI Chopping Block, Inc.; New York, Northern (NY, KY); Hybride; USD 180 000 - 240 000; Plein temps

Résumé du poste

Mecka AI is building the data infrastructure layer for robotics and embodied AI. This hands-on research engineering role focuses on constructing reinforcement learning environments, writing working software, and collaborating with product colleagues and domain experts to advance evaluation tools.

You will work with engineers to turn research prototypes into reusable environments, ensure experiments are reproducible, and communicate tradeoffs and findings clearly.

Qualifications

• Hands-on experience formulating RL tasks and constructing environments.
• Strong programming and debugging to build reusable research systems.
• Good experimental design and statistical reasoning with controlled comparisons.
• Ability to reason about environment dynamics and reward design.
• Independent research judgment and clear communication.

Responsabilités

• Build environments: define tasks, observations, actions and state transitions.
• Develop rewards and scoring: translate objectives into feedback and evaluation criteria.
• Run learning experiments: implement baseline agents, train and compare policies.
• Make evaluation reliable: separate training and held-out tasks, report uncertainty and performance.
• Investigate failures: inspect trajectories to identify root causes and inform next steps.
• Build with the team: validate assumptions with domain experts and turn prototypes into reusable tools.

Connaissances

RL environment expertise

Programming & debugging

Experimental design

Environment dynamics

Independent research judgment

Description du poste

About Mecka AI

Mecka AI is building the data infrastructure layer for robotics and embodied AI.
We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems.
We work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware.

Build reinforcement learning environments that help researchers train models and understand their capabilities. Across Mecka's Labs team, you'll translate real tasks into computational problems, implement environments for model training and test whether measured progress reflects useful behavior.

This is a hands-on research engineering role for someone who knows how to construct reinforcement learning environments. You'll write working software, investigate failures and develop methods with product colleagues, domain experts and engineers.

What you will be doing:

• Build environments: Define tasks, observations, actions and state transitions. Implement reset behavior, termination conditions and measurable outcomes in environments agents can interact with.

• Develop rewards and scoring: Translate task objectives into feedback and evaluation criteria. Test whether agents can exploit scoring rules without completing the intended task.

• Run learning experiments: Implement baseline agents, train and compare policies, and design controlled experiments that isolate the effects of data, methods and environment changes.

• Make evaluation reliable: Separate training and held-out tasks, check for leakage, version experiments and repeat runs. Report uncertainty and performance across conditions alongside aggregate scores.

• Investigate failures: Inspect trajectories and learning behavior to distinguish policy limitations from data, reward or environment problems. Use findings to prioritize the next experiment.

• Build with the team: Work with domain experts to validate task assumptions and with engineers to turn research prototypes into reusable environments, evaluation tools and documented methods.

What you bring:

• RL environment expertise: You have hands‑on experience formulating problems, constructing environments, training agents and critically assessing results.

• Strong programming and software debugging skills; able to build and test research systems that other people can run and extend.

• Sound experimental design and statistical reasoning, including controlled comparisons, evaluation splits, variability and the limits of benchmark results.

• Ability to reason about environment dynamics, reward design and agent behavior, but trace unexpected results to concrete causes.

• Independent research judgment and clear communication; learn unfamiliar domains, work with specialists and explain assumptions, tradeoffs and findings.

Even better if you have:

• Experience building interactive environments, simulators or benchmarks used by other researchers.

• Work on agent evaluation, reward design and imitation learning or learning from real-world data.

• Research artifacts with reproducible experiments, useful baselines and evidence of investigating failures beyond headline scores.

Inclusive Hiring at Mecka

We are committed to creating an inclusive and supportive candidate experience. Should you require any accommodation whatsoever during the interview process, please inform us without any hesitation. Mecka is dedicated to ensuring equal treatment and opportunity in all phases of recruitment, selection, and employment, in compliance with employment law. We do not discriminate based on gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other protected category. Mecka is proud to be an equal opportunity employer, fostering a culture of inclusivity and maintaining a work environment that is free from discrimination, harassment, and retaliation.

Use of Artificial Intelligence in Recruitment

Mecka uses artificial intelligence (AI) responsibly to support administrative and efficiency-focused aspects of our recruitment process. This includes activities such as drafting job descriptions, generating interview questions, note‑taking and recordings, and supporting sourcing and scheduling workflows. All candidate evaluations, interviews, and hiring decisions are made by members of the Mecka team. While AI tools may assist with screening and assessment, they do not replace human judgment in selection decisions. Our use of AI is intended to streamline routine tasks, improve consistency, and enhance the overall candidate experience. We are committed to upholding principles of fairness, transparency, and accountability in all hiring activities. Mecka regularly reviews its recruitment practices to mitigate bias and to ensure alignment with applicable laws and evolving best practices.