--- title: 'AI Researcher at 1X' canonical: 'https://feeny.ai/job/ai-researcher-1x-san-carlos-geej7nd5frgp' type: 'job' last_seen: '2026-09-13' --- # AI Researcher at 1X - **Company:** [1X](https://feeny.ai/companies/1x) - **Location:** San Carlos, CA - **Compensation:** $250k–$350k - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-06-17 - **Last confirmed live:** 2026-09-13 - **Apply:** https://jobs.ashbyhq.com/1x/2d0f6eec-6e64-403f-baf7-330fe81b1473/application **Skills:** Python, PyTorch, Deep Learning, Large-scale codebases, Data tooling, Data visualization, TorchTitan, DeepSpeed, FSDP, ZeRO, Large-scale data processing pipelines, ETL systems, Multi-modal generative models, World models, Diffusion models, Autoregressive architectures, Inference optimization, Quantization (PTQ, QAT, INT8/FP8), CUDA, Triton kernel development > Join the 1X World Model Lab to advance embodied AI research by building large-scale multi-modal generative world models, data infrastructure, and ML systems. The role involves conducting frontier research, optimizing training throughput, and shipping research to production on robot hardware. ## Job description ## About the Lab The 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. The 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. ## Your Charter Advance 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. The key pillars of AI are: Model and Data Build 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! Data Infrastructure and Tooling Design 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! ML Infrastructure Own 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! Evaluations Build 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! ## Key Outcomes - Advance robot capabilities through research, scaling data pipelines, optimizing training and inference throughput, or building evaluations that make lab results predictive of field performance - Build 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 - Ship 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 - Contribute 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 ## Key Competencies - 0 → 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 - Full-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 - Research 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 - Scale-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 - Fast 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 ## Minimum Requirements - Strong Python and PyTorch (or equivalent deep learning framework), with experience in large-scale codebases and data tooling and visualization - Demonstrated experience in at least one area of the four pillars of AI: model and data, data infrastructure, ML infrastructure, or evaluation protocols - Degree in Computer Science, Machine Learning, or a related field; graduate-level education or equivalent research experience strongly preferred - Track record of impact: published research, deployed production in modern AI systems, or infrastructure that measurably accelerated a team's work ## Preferred Skills - Experience 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 - Experience with multi-modal generative models, world models, diffusion models, or autoregressive architectures - Experience with inference optimization techniques: quantization (PTQ, QAT, INT8/FP8), CUDA/Triton kernel development, or serving systems (TensorRT or equivalent) ## Benefits & Compensation - Salary Range: $250,000 - $350,000 + competitive equity - Health, dental, and vision insurance - 401(k) with company match - Paid time off and holidays ## Equal Opportunity Employer 1X 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. ## About 1X ## Company Overview - **One-liner**: 1X develops general-purpose humanoid robots for home and industrial environments, combining AI and hardware to automate everyday tasks. - **Entity Type**: Private (Series B funding stage) - **Headquarters**: Palo Alto, California, United States - **Founded**: 2015 - **Founders**: Bernt Øyvind Børnich ## Core Business - **Primary industry**: Robotics Engineering / Artificial Intelligence - **Target customers**: B2C (home consumers via NEO) and B2B/Enterprise (industrial tasks via EVE) - **Mission**: Build a truly abundant society through general-purpose robots capable of performing any kind of work autonomously, allowing humans to focus on what they love. ## Products & Services - **NEO**: A friendly home humanoid robot designed to integrate seamlessly into daily life and handle chores. Currently in early access after the NEO Beta (2024) and NEO Gamma (2025) iterations. [1x.tech](https://www.1x.tech/about) - **EVE**: A wheeled industrial humanoid deployed in factories worldwide for autonomous industrial tasks. [1x.tech](https://www.1x.tech/about) - **Revo1**: A high-torque-to-weight drive servo motor inspired by human tendon actuation, used in 1X robots. [1x.tech](https://www.1x.tech/about) - **1X World Model**: A physics-grounded video model that enables NEO to learn autonomously from text or voice commands. [linkedin.com](https://www.linkedin.com/company/1x-technologies) ## Market Standing - **Valuation**: Not publicly disclosed - **Key Metric**: Total funding of $169M as of mid-2026, with a $100M Series B led by EQT Ventures in January 2024. [linkedin.com](https://www.linkedin.com/company/1x-technologies) - **Notable Investors/Partners**: EQT Ventures (lead), plus other investors in secondary rounds. Acquired Kind Humanoid in January 2025. [linkedin.com](https://www.linkedin.com/company/1x-technologies) - **Growth Signals**: - Headcount grew 121.2% YoY to 394 employees. [linkedin.com](https://www.linkedin.com/company/1x-technologies) - Full-scale production of NEO began in Hayward, CA, with capacity to build 10,000 units per year. [linkedin.com](https://www.linkedin.com/company/1x-technologies) - New Palo Alto HQ consolidated teams from Sunnyvale and Moss, Norway. [linkedin.com](https://www.linkedin.com/company/1x-technologies) - Appointed Mohi Khansari as Head of Robot Learning (January 2026) and Vikram Kothari as VP of Operations (August 2025). [linkedin.com](https://www.linkedin.com/company/1x-technologies) ## Competitive Advantages - **Vertical integration**: Owns manufacturing in Hayward (U.S.) and Moss (Norway), controlling the full production stack. - **Proprietary hardware**: Revo1 servo motor offers world-leading torque-to-weight ratio, enabling flexible, low-gear-ratio robotics. - **AI-first approach**: The 1X World Model allows robots to learn physical tasks via simulation and self-supervised video prediction, reducing need for manual programming. - **Early home deployment**: NEO is one of the first humanoid robots entering private homes, giving 1X real-world data and feedback loops. ## Strategic Focus - Scaling NEO production and expanding early access to more households across the U.S. - Enhancing AI capabilities through the World Model and reinforcement learning (e.g., Redwood mobility controller). - Building a robust supply chain and service network for home robots. - Continuing enterprise deployments of EVE while shifting emphasis to the consumer market. ## Why Work Here - **Culture**: Fast-paced, mission-driven environment focused on building humanoid robots that coexist with humans. Strong emphasis on AI, hardware, and real-world impact. - **Work model**: Likely on-site for hardware and AI roles (multiple offices in Palo Alto, San Carlos, Sunnyvale, Hayward, and Moss). Some software roles may offer flexibility. - **Notable perks**: Opportunity to work on cutting-edge robotics and AI, contribute to a product (NEO) that is already entering homes, and be part of a rapidly scaling company with strong funding. - **Engineering culture**: High concentration of talent from Tesla, Apple, Google, and SpaceX. Active research in biomechanics, reinforcement learning, and simulation. [linkedin.com](https://www.linkedin.com/company/1x-technologies) - **Open roles**: 65+ positions listed on the careers page across AI, hardware, software, operations, and manufacturing. [1x.tech](https://www.1x.tech/careers) ## Sources 1. [1x.tech](https://www.1x.tech/about) 2. [1x.tech](https://www.1x.tech/careers) 3. [linkedin.com](https://www.linkedin.com/company/1x-technologies) ## Other roles at 1X - [Motor Test Technician](https://feeny.ai/job/motor-test-technician-1x-san-carlos-zsyhcdhha6ew) — San Carlos, CA - [Operator - Data Collection (Swing Shift)](https://feeny.ai/job/operator-data-collection-swing-shift-1x-san-carlos-36y5yx97sgj2) — San Carlos, CA - [Test Technician](https://feeny.ai/job/test-technician-1x-san-carlos-nz09g8sf00e1) — San Carlos, CA - [Workplace Coordinator](https://feeny.ai/job/workplace-coordinator-1x-san-carlos-ytfpx1cnvcdr) — San Carlos, CA - [Test Technician Battery](https://feeny.ai/job/test-technician-battery-1x-san-carlos-gkv567tacry3) — San Carlos, CA - [Mechanical Engineer](https://feeny.ai/job/mechanical-engineer-1x-san-carlos-y9p7cxq0shp5) — San Carlos, CA - [CAD Modeler](https://feeny.ai/job/cad-modeler-1x-san-carlos-hwxaw6xckapg) — San Carlos, CA - [Test Engineer](https://feeny.ai/job/test-engineer-1x-hayward-ws0qnjx1vfcd) — Hayward, CA - [Principal Safety Engineer](https://feeny.ai/job/principal-safety-engineer-1x-san-carlos-1j6pqzt2rstz) — San Carlos, CA - [Facilities Technician](https://feeny.ai/job/facilities-technician-1x-san-carlos-dgdbcx0b1bdn) — San Carlos, CA