{"id":3144977,"url":"https://alion.io/job/phyagents-ml-engineer-robotics","title":"ML Engineer - Robotics","company":{"id":4465011,"name":"PhyAgents","domain":"phyagents.com","url":"https://alion.io/company/phyagents","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Robotics","role_family":"Robotics","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":47000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":133},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"DeepSpeed","optional":false},{"name":"Diffusion Models","optional":false},{"name":"FSDP","optional":false},{"name":"Imitation Learning","optional":false},{"name":"Isaac Sim","optional":false},{"name":"Machine Learning","optional":false},{"name":"MuJoCo","optional":false},{"name":"Multimodal AI","optional":false},{"name":"ONNX","optional":false},{"name":"Post-training","optional":false},{"name":"PyBullet","optional":false},{"name":"PyTorch","optional":false},{"name":"Ray","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Sim-to-Real","optional":false},{"name":"TensorRT","optional":false},{"name":"Vision-Language-Action","optional":false}],"status":"live","first_seen_at":"2026-10-23T09:35:15Z","employer_posted_date":null,"last_verified_at":"2026-10-23T09:35:15Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"At PhyAgents, a machine learning engineer works across the full loop that makes a robot better: data, models, training, simulation, evaluation, and deployment on real hardware. You'll do research-grade work and ship it onto robots in the same quarter. A result that doesn't run on the robot isn't finished.\n\nResponsibilities: \nTraining and post-training: Train and post-train robotic foundation models, including vision-language-action models, using imitation learning and reinforcement learning. You'll own the work from data loading through multi-GPU training runs.\nTraining infrastructure: Build and scale distributed multi-node GPU training, data loaders that keep GPUs fed, and reproducible pipelines with experiment tracking.\nSimulation: Build simulation environments for our tasks. Train policies with reinforcement learning that transfer to real robots.\nRewards and verifiers: Design the reward functions and the verifiers that check whether a task step actually succeeded.\nEvaluation: Build harnesses that tell us whether a model actually got better, in simulation and on real hardware. Design the metrics that decide what ships.\nData and data infrastructure: Define what data the models need. Build the pipelines that turn raw robot episodes into versioned, training-ready datasets. Trace a stuck policy back to its data.\nModels on robots: Get models running reliably and fast enough on real hardware. Debug failures in the lab across the model, the data, and the robot.\n\nRequirements: \n5+ years of hands-on experience training and shipping ML models in production or in a research lab, with a B. Tech, M. Tech or PhD in Computer Science, Electrical Engineering or a related field.\nA track record of owning an ML system end to end: you've taken something from problem definition through data, training, evaluation, and deployment, and you can tell us what you'd do differently.\nDeep hands-on experience with PyTorch, including writing and debugging non-trivial training loops.\nExperience training at scale: multi-GPU or multi-node training (DDP, FSDP, DeepSpeed, or equivalent) and the profiling work to keep it efficient.\nStrong fundamentals in linear algebra, probability, optimisation, and machine learning, and in data structures, algorithms, and systems.\nStrong software engineering habits: you write code others can build on, and hold a high bar for code quality.\n\nPreferred: \nExperience post-training transformers, diffusion models, or multimodal models, especially with imitation learning or reinforcement learning.\nExperience in robotics, autonomous vehicles, or another domain where models act in the physical world and failures are expensive.\nExperience with robot simulation (MuJoCo, Isaac Sim, PyBullet) and sim-to-real transfer.\nExperience building data pipelines for large multimodal datasets (object storage, Ray or Spark, Parquet, WebDataset).\nExperience deploying models to constrained or real-time hardware (ONNX, TensorRT, quantisation, latency work).\nPublications at top AI or robotics venues, or meaningful open-source contributions.\nExperience mentoring engineers or leading a small technical effort.\nSkills\nML, PyTorch, machine learning, robotics","description_format":"text","description_chars":3180,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-23T09:35:15Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":2,"expected_fill_days":23,"reasons":["seen:2","win:early"],"computed_at":"2026-10-26T05:57:25Z"},"pay":null,"html_url":"https://alion.io/job/phyagents-ml-engineer-robotics","json_url":"https://alion.io/job/phyagents-ml-engineer-robotics.json","meta":{"generated_at":"2026-10-26T10:29:36Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":14038,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-27T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":4465011},"rest":"https://alion.io/mcp/rest/get_company?id=4465011"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fphyagents-ml-engineer-robotics"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fphyagents-ml-engineer-robotics"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fphyagents-ml-engineer-robotics"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/phyagents-ml-engineer-robotics\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fphyagents-ml-engineer-robotics"}]}