{"id":127459,"url":"https://alion.io/job/1x-technologies-ai-researcher","title":"AI Researcher","company":{"id":47967,"name":"1X Technologies","domain":"1x.tech","url":"https://alion.io/company/1x-technologies","size_band":"51-200","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":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":["San Carlos, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":250000,"max":350000,"currency":"USD","period":"year","gross":null,"usd_annual":350000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Embodied AI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Pre-training","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Tokenization","optional":false},{"name":"World Models","optional":false},{"name":"CUDA","optional":true},{"name":"CUDA Toolkit","optional":true},{"name":"DeepSpeed","optional":true},{"name":"Diffusion Models","optional":true},{"name":"ETL/ELT","optional":true},{"name":"FSDP","optional":true},{"name":"Quantization","optional":true},{"name":"TensorRT","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2026-06-17T00:13:57Z","employer_posted_date":"2026-06-17","last_verified_at":"2026-10-19T23:49:56Z","board_verified":true,"closed_at":null,"days_open":125,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":125},"description":"About the Lab\nThe 1X World Model Lab is an embodied AI research organization focused on pretraining the foundation models to accelerate the emergence of embodied intelligence. As the lab grows, researchers contribute where they have the most leverage, and the problems worth solving span every layer of the stack.\nThe lab is founded on a simple thesis:robotics is not a fine-tuning problem. To build truly general humanoids, we need to pretrain on the most important data from the very beginning.\nYour Charter\nAdvance NEO's intelligence by building the AI systems, infrastructure, and data engines that enable the robot to learn from experience and become increasingly capable in real-world environments.\nThe key pillars of AI are:\nModel and Data\nBuild large multi-modal generative world models that learn from robot experience, spanning model architecture, tokenization, and large-scale training and data processing. Advance the robot's ability to predict, plan, and act in unstructured environments. Simply: good tokens in = good tokens out!\nData Infrastructure and Tooling\nDesign and operate the data engine that enables training on all visual and robot data. From web-scale media, to egocentric and synthetic data, and most importantly, on-policy NEO data, building large-scale data infrastructure that enables annotation and curation at scale, are crucial to scale up World Model training. Simply: more tokens in = more tokens out!\nML Infrastructure\nOwn the distributed training and inference systems that keep GPUs fully utilized. Increase the throughput during training, and speed of inference, to supercharge the model’s ability in the lab and in the world. Simply: more tokens seen = better tokens out!\nEvaluations\nBuild the evaluation infrastructure that connects pre-training metrics to real-world robot performance: benchmarks, evals frameworks, model ranking systems, and the tooling that lets the team iterate on architectures with confidence that lab results predict what happens in the the real physical world. Simply: more tokens evaluated = better model performance!\nKey Outcomes\nAdvance robot capabilities through research, scaling data pipelines, optimizing training and inference throughput, or building evaluations that make lab results predictive of field performance\n\nBuild infrastructure that multiplies team research velocity: pipelines that are faster, evaluations that are more predictive, training systems that are more efficient, or tooling that eliminates manual work across the lab\n\nShip research to production: own the path from experimental result to deploy capability on robot hardware, and measure impact by what NEO can do, not just what the model achieves on benchmarks\n\nContribute to a learning flywheel where more robot experience leads to better models, better models enable more capable robots, and more capable robots generate richer experience\n\nKey Competencies\n0 → 1 mentality excited to build systems from scratch that can efficiently ingest hundreds of millions of hours of videos, and excited to work through the tough and gritty aspects of engineering\n\nFull-stack ML thinker understanding the path from raw robot data to trained model to deployed policy, and can identify and address bottlenecks at any layer of that stack: data quality, training efficiency, model architecture, or inference performance\n\nResearch depth plus engineering rigor conducting frontier research and builds systems others depend on; doesn't treat production engineering as someone else's job, and pushes work past promising training curves to deployed capabilities\n\nScale-first mindset believing scale is foundational to capable humanoid robotics; designs systems with 10x and 100x growth in mind, and actively pushes to remove whatever is currently the binding constraint on model improvement\n\nFast and high-agency contributor picking up new domains and codebases quickly, identifies the highest-leverage contribution, and makes meaningful progress without waiting for a detailed spec\n\nMinimum Requirements\nStrong Python and PyTorch (or equivalent deep learning framework), with experience in large-scale codebases and data tooling and visualization\n\nDemonstrated experience in at least one area of the four pillars of AI: model and data, data infrastructure, ML infrastructure, or evaluation protocols\n\nDegree in Computer Science, Machine Learning, or a related field; graduate-level education or equivalent research experience strongly preferred\n\nTrack record of impact: published research, deployed production in modern AI systems, or infrastructure that measurably accelerated a team's work\n\nPreferred Skills\nExperience with distributed training frameworks (TorchTitan, DeepSpeed, FSDP/ZeRO) and/or large-scale data processing pipeline and ETL systems spanning on-device, on-premise, and cloud infrastructure\n\nExperience with multi-modal generative models, world models, diffusion models, or autoregressive architectures\n\nExperience with inference optimization techniques: quantization (PTQ, QAT, INT8/FP8), CUDA/Triton kernel development, or serving systems (TensorRT or equivalent)\n\nBenefits & Compensation\nSalary Range: $250,000 - $350,000 + competitive equity\n\nHealth, dental, and vision insurance\n\n401(k) with company match\n\nPaid time off and holidays\n\nEqual Opportunity Employer\n1X is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, ancestry, citizenship, age, marital status, medical condition, genetic information, disability, military or veteran status, or any other characteristic protected under applicable federal, state, or local law.","description_format":"text","description_chars":5749,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Vision insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Robotics AI","Humanoid Robots"],"lifecycle":[{"event":"open","at":"2026-06-17T00:13:57Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 12","filings_12m":12,"filings_prev_12m":0,"green_card_filings_12m":0,"median_offered_wage_usd":177500,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":1}],"liveness":{"score":24,"band":"cold","label":"Long shot","p_open":1,"p_active":0.549,"p_room":0.44,"age_days":124,"expected_fill_days":84,"reasons":["conf:1","velocity","win:tail","crowd:"],"computed_at":"2026-10-19T05:45:15Z"},"pay":{"stated_usd_annual":350000,"is_top_pay":true},"html_url":"https://alion.io/job/1x-technologies-ai-researcher","json_url":"https://alion.io/job/1x-technologies-ai-researcher.json","meta":{"generated_at":"2026-10-20T00:32:24Z","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":572,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-21T00:00:00Z"}},"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":47967},"rest":"https://alion.io/mcp/rest/get_company?id=47967"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2F1x-technologies-ai-researcher"},{"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%2F1x-technologies-ai-researcher"},{"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%2F1x-technologies-ai-researcher"},{"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/1x-technologies-ai-researcher\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2F1x-technologies-ai-researcher"}]}