{"id":1115389,"url":"https://alion.io/job/nidus-staff-ml-engineer-vla-training","title":"Staff ML Engineer, VLA Training","company":{"id":682361,"name":"Nidus","domain":"nidus.tech","url":"https://alion.io/company/nidus-2","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","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"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":187000,"max_usd":371000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":890},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Imitation Learning","optional":false},{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Post-training","optional":false},{"name":"PyTorch","optional":false},{"name":"Vision-Language-Action","optional":false},{"name":"FSDP","optional":true},{"name":"Gazebo","optional":true},{"name":"Isaac Sim","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"Model Distillation","optional":true},{"name":"MuJoCo","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"ROS","optional":true},{"name":"Tokenization","optional":true},{"name":"World Models","optional":true}],"status":"live","first_seen_at":"2026-09-22T14:46:44Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-11-10T01:54:32Z","board_verified":true,"closed_at":null,"days_open":48,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":48},"description":"About Us\nNidus is building autonomous manufacturing systems powered by AI and robotics. U.S. manufacturers are under growing pressure to increase output while navigating workforce constraints, underutilized equipment, and increasingly complex supply chains. We believe the next generation of manufacturing will be enabled by more intelligent, flexible automation-systems that help people and machines work together to expand capacity and improve productivity.\nWe're building the intelligence layer that makes that possible.\nOur team comes from the intersection of defense technology and AI. We've built and shipped products to DoD customers, and we bring deep experience across ML, robotics, product development, and defense.\nWe're a small, in-person team in New York City working on hard problems that matter. If you want to build the future of American manufacturing, we'd love to hear from you.\nAbout the role\nWe are building intelligent robots that can perceive the world, understand instructions, and perform useful physical tasks in dynamic, real-world environments.\nWe are looking for a Staff Machine Learning Engineer to develop and scale the vision-language-action models that power our robots. You will own major parts of the model development lifecycle-from dataset construction and training recipes to distributed training infrastructure, evaluation, and on-robot validation.\nThis is a hands-on role at the intersection of machine learning research, large-scale systems, and robotics. You will work closely with researchers, robotics engineers, data teams, and operators to turn new modeling ideas into reliable robot capabilities. The right person is equally comfortable investigating why a policy failed on a robot, designing the next training experiment, and improving the infrastructure required to run that experiment efficiently at scale.\nWhat you’ll do\nTrain and improve vision-language-action models for robotic manipulation and other embodied tasks.\n\nDevelop model architectures and training recipes spanning imitation learning, behavior cloning, transformer- and diffusion-based policies, multimodal pretraining, and post-training.\n\nBuild scalable pipelines for pretraining, fine-tuning, evaluation, checkpointing, and model release.\n\nTrain models across multi-node GPU clusters while improving utilization, throughput, stability, and cost efficiency.\n\nDesign data mixtures, sampling strategies, augmentations, and curriculum approaches for large, heterogeneous robot datasets.\n\nDevelop data loaders and preprocessing systems for synchronized video, language, robot state, actions, and other sensor modalities.\n\nCreate reproducible experimentation systems, including configuration management, dataset and model versioning, experiment tracking, and automated regression testing.\n\nDefine offline and on-robot metrics that measure task success, generalization, robustness, latency, safety, and failure modes.\n\nBuild tools for inspecting trajectories, visualizing model behavior, comparing experiments, and diagnosing data or training failures.\n\nRun structured experiments on physical robots and use the results to guide model, data, and infrastructure improvements.\n\nPartner with data collection teams to identify coverage gaps, improve demonstration quality, and prioritize collection based on model performance.\n\nTranslate promising research into maintainable, production-quality systems that can support repeated deployment across robots and environments.\n\nMake technical decisions across model architecture, data, compute, and evaluation, and communicate the associated tradeoffs clearly.\n\nMentor other engineers and establish strong engineering practices for the ML codebase.\n\nWhat we’re looking for\nFive or more years of professional experience in machine learning, robotics, computer vision, or a closely related field, or equivalent demonstrated impact.\n\nStrong experience training modern deep learning models using PyTorch, JAX, or a comparable framework.\n\nExperience with transformer-based models, multimodal models, generative models, or learned control policies.\n\nExperience building and operating distributed training pipelines on multi-GPU or multi-node accelerator clusters.\n\nExperience with large-scale datasets, high-throughput data loading, experiment tracking, and reproducible ML workflows.\n\nStrong understanding of optimization, model architecture, data quality, evaluation methodology, and experimental design.\n\nAbility to debug failures across the full stack, from input data and training dynamics to inference and robot behavior.\n\nExperience independently owning technically ambiguous projects and delivering working systems.\n\nClear communication skills and an ability to collaborate across research, infrastructure, robotics, hardware, and operations teams.\n\nA bachelor’s degree in computer science, machine learning, robotics, electrical engineering, or a related field-or equivalent practical experience.\n\nNice to have\nExperience developing vision-language-action models, vision-language models, or robotics foundation models.\n\nExperience with imitation learning, reinforcement learning, behavior cloning, diffusion policies, action tokenization, or action-conditioned world models.\n\nExperience training policies using data from multiple robot embodiments, task domains, or sensor configurations.\n\nFamiliarity with large-scale pretraining, post-training, parameter-efficient fine-tuning, distillation, or model adaptation.\n\nExperience optimizing distributed training using techniques such as FSDP, tensor or pipeline parallelism, mixed precision, gradient checkpointing, or sharded data loading.\n\nFamiliarity with robotics middleware and simulation environments such as ROS/ROS 2, MuJoCo, Isaac Sim, or Gazebo.\n\nExperience deploying and evaluating learned policies on physical robotic systems.\n\nPublications or meaningful open-source contributions in machine learning, robotics, computer vision, or related areas.\n\nNidus Technologies is an equal opportunity employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status.\nWe encourage candidates from all backgrounds to apply, even if you don't feel like you're a perfect fit. If you're passionate about contributing to our mission, we'd love to hear from you!","description_format":"text","description_chars":6452,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Defense Manufacturing","Industrial AI"],"lifecycle":[{"event":"open","at":"2026-09-22T15:14:07Z"}],"visa":[],"liveness":{"score":36,"band":"fade","label":"Fading","p_open":1,"p_active":0.648,"p_room":0.55,"age_days":47,"expected_fill_days":32,"reasons":["conf:0","win:tail"],"computed_at":"2026-11-09T06:03:00Z"},"pay":null,"html_url":"https://alion.io/job/nidus-staff-ml-engineer-vla-training","json_url":"https://alion.io/job/nidus-staff-ml-engineer-vla-training.json","meta":{"generated_at":"2026-11-10T04:28:40Z","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":10424,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-11T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"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":682361},"rest":"https://alion.io/mcp/rest/get_company?id=682361"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fnidus-staff-ml-engineer-vla-training"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":2,"usd":0.2},"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%2Fnidus-staff-ml-engineer-vla-training"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"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%2Fnidus-staff-ml-engineer-vla-training"},{"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/nidus-staff-ml-engineer-vla-training\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fnidus-staff-ml-engineer-vla-training"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":1115389}},{"tool":"search_jobs","arguments":{"company":"nidus.tech","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":1115389},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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