{"id":2038672,"url":"https://alion.io/job/mecka-research-engineer-simulation-world-models","title":"Research Engineer, Simulation & World Models","company":{"id":678757,"name":"Mecka","domain":"mecka.ai","url":"https://alion.io/company/mecka","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":95,"open_postings":14,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":109,"computed_at":"2026-10-10T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States","San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":170000,"max":300000,"currency":"USD","period":"year","gross":null,"usd_annual":300000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Embodied AI","optional":false},{"name":"Isaac Sim","optional":false},{"name":"MuJoCo","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Sim-to-Real","optional":false},{"name":"Synthetic Data","optional":false},{"name":"World Models","optional":false}],"status":"live","first_seen_at":"2026-10-07T15:33:50Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-11T21:55:42Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"About Mecka AI\nMecka AI is building the data infrastructure layer for robotics and embodied AI.\nWe 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.\nWe work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware.\nBuild simulation systems that train and evaluate robots and embodied agents. Model physical interactions, create scalable training worlds and connect simulation with real-world data across Mecka Labs.\nThis is a hands-on research engineering role for someone exceptional in simulation, physics and learning. You'll work with MuJoCo, Isaac Sim and related tools, close sim-to-real gaps, and build learned or hybrid world models for prediction, planning and control. You own whether the simulated world behaves credibly and runs at scale; partner roles turn it into trainable tasks and reliable evaluations.\nWhat you will be doing:\nBuild simulation environments: Model robots, sensors, objects, contacts, materials and dynamics, with scenarios grounded in real behavior.\n\nScale training workloads: Build reliable pipelines for parallel rollouts, synthetic data, policy training and evaluation.\n\nImprove physical fidelity: Calibrate against measured data, find mismatches in dynamics or sensing and make targeted improvements.\n\nDrive sim-to-real: Use system identification, domain randomization and controlled experiments to improve transfer.\n\nDevelop world models: Build learned dynamics or latent models, combine them with physics-based systems and test their value for prediction, planning and control.\n\nBuild with the team: Turn prototypes into reusable simulation assets, training infrastructure and documented methods with researchers and engineers.\n\nWhat you bring:\nSimulation and physics: Deep experience building and debugging physics-based simulation with MuJoCo, Isaac Sim or comparable platforms.\n\nRobotics learning: Strong reinforcement learning and embodied AI fundamentals, including observations, actions, rewards and policy evaluation.\n\nWorld models: Experience with learned dynamics, latent world models or hybrid physics-learning systems.\n\nResearch engineering: Strong Python and C++ systems skills; you build scalable, reproducible tools other researchers can extend.\n\nExperimental judgment: Design controlled experiments, measure sim-to-real gaps and trace failures to models, data, policies or infrastructure.\n\nEven better if you have:\nSimulation or training infrastructure used at scale by a robotics or embodied AI research team.\n\nDemonstrated sim-to-real transfer in manipulation, locomotion, navigation or another physical domain.\n\nPublished or open-source work in world models, differentiable simulation, GPU-accelerated simulation or model-based reinforcement learning.\n\nA Note on Applying\nStudies show women and candidates from underrepresented groups often only apply when they meet 100% of the listed qualifications, while others apply after meeting 60%. If you don't check every box above but believe you can do the job, we encourage you to apply - we're looking for capability and trajectory, not a perfect checklist match.\nInclusive Hiring at Mecka\nWe 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.\nUse of Artificial Intelligence in Recruitment\nMecka 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. 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