AI Research Engineer - Infrastructure

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  "description": "<p><strong><span style=\"color:#9a9da9\">AI Research Engineer - Infrastructure</span></strong></p><p><strong><span style=\"color:#9a9da9\">San Carlos, CA (on-site)</span></strong></p><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">About 1X</span></strong></p><p><span style=\"color:#9a9da9\">We’re building humanoid robots that work in home - doing the chores, handling the tasks, and giving people their time back. Simple, but it’s not.&nbsp;</span></p><p style=\"min-height: 1.7em;\"></p><p><span style=\"color:#9a9da9\">To do this right, we have to solve robotics, AI, manufacturing - at the same time, at scale, in a form factor that has to be safe enough to live with your family. If you’re inspired by this, you’ll thrive here. We’ve been at this since 2014 and we’re at the point where the hard problems are behind us and the hard work is in front of us.&nbsp;<br></span></p><p><span style=\"color:#9a9da9\">NEO is our flagship - a home robot designed to move, learn, and operate in the real world alongside real people. We’re not demoing it - we’re shipping it. We’re excited to meet you, if this excites you.&nbsp;</span></p><p style=\"min-height: 1.7em;\"></p><p><span style=\"color:#9a9da9\">If you’ve spent your career working on problems that matter and want to see them actually reach the world - this is that moment. We’re scaling, we’re hiring with intention, and we need people who want to build something that will genuinely change how humans spend their time - safely creating abundance for all.&nbsp;</span></p><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">About the Team</span></strong></p><p><span style=\"color:#9a9da9\">The 1X World Model Lab is an embodied AI research organization focused on pretraining the foundation models to accelerate the emergence of embodied intelligence.<br></span></p><p><span style=\"color:#9a9da9\">The lab is founded on a simple thesis: </span><strong><em><span style=\"color:#9a9da9\">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.</span></em></strong></p><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Your Charter</span></strong></p><p><span style=\"color:#9a9da9\">Own the infrastructure that enables 1X's AI to improve continuously at scale, spanning the data pipelines that make fleet experience training-ready and the distributed training and inference systems that turn data into capability. This is critical-path work: the speed at which 1X's robots learn is directly determined by how efficiently we collect high-quality data, how reliably we run large training jobs, and how effectively we deploy the resulting models to hardware. Depending on your background and interests, you will focus on data infrastructure, compute scaling, or both.</span></p><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Key Outcomes</span></strong></p><ul><li><p><span style=\"color:#9a9da9\">Build and operate data pipelines that make fleet-collected robot experience consistently queryable, well-labeled, and training-ready, automating ETL across on-robot, on-premise, and cloud infrastructure</span></p></li><li><p><span style=\"color:#9a9da9\">Own distributed training infrastructure that supports GPU runs reliably: fault tolerance, experiment tracking, throughput optimization, and distributed operations at scale</span></p></li><li><p><span style=\"color:#9a9da9\">Optimize inference performance for both datacenter workloads (world models, diffusion engines) and on-device robot policies, using quantization, scheduling, and distillation to reduce latency and improve throughput</span></p></li><li><p><span style=\"color:#9a9da9\">Deliver annotation and dataset tooling: visualization interfaces, labeling automation, ML-based dataset organization that accelerates the data-to-model cycle for the research team</span></p></li><li><p><span style=\"color:#9a9da9\">Ensure compute is never the constraint: design systems where data quality and quantity, not infrastructure bottlenecks, determine the limits of what the models can learn</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Key Competencies</span></strong></p><ul><li><p><strong><span style=\"color:#9a9da9\">Scale-first mindset </span></strong><span style=\"color:#9a9da9\">believes scale is foundational to capable humanoid robotics; designs systems with 10x and 100x growth in mind, and pushes to remove whatever is currently the binding constraint on model improvement</span></p></li><li><p><strong><span style=\"color:#9a9da9\">Full-pipeline thinker </span></strong><span style=\"color:#9a9da9\">understands the path from robot sensor to trained model and can reason about bottlenecks at every layer: data collection, labeling quality, training throughput, and inference latency</span></p></li><li><p><strong><span style=\"color:#9a9da9\">Hands-on optimizer </span></strong><span style=\"color:#9a9da9\">comfortable writing CUDA or Triton kernels, tuning distributed training configurations, or redesigning ETL pipelines, whichever layer needs work</span></p></li><li><p><strong><span style=\"color:#9a9da9\">Production-minded researcher </span></strong><span style=\"color:#9a9da9\">transforms experimental systems into reliable, production-grade platforms; brings engineering rigor to infrastructure that other teams depend on every day</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Benefits &amp; Compensation</span></strong></p><ul><li><p><span style=\"color:#9a9da9\">Salary Range: $180,000 - $300,000 + Equity</span></p></li><li><p><span style=\"color:#9a9da9\">Health, dental, and vision insurance</span></p></li><li><p><span style=\"color:#9a9da9\">401(k) with company match</span></p></li><li><p><span style=\"color:#9a9da9\">Paid time off and holidays</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Equal Opportunity Employer</span></strong></p><p><span style=\"color:#9a9da9\">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.</span></p>",
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  "requirements": "<p><strong><span style=\"color:#9a9da9\">Minimum Requirements</span></strong></p><ul><li><p><span style=\"color:#9a9da9\">Strong programming experience in Python and/or C++</span></p></li><li><p><span style=\"color:#9a9da9\">Degree in Computer Science or a related field</span></p></li><li><p><span style=\"color:#9a9da9\">Experience in distributed training frameworks (e.g., TorchTitan, DeepSpeed, FSDP/ZeRO) and/or large-scale data pipeline and ETL systems</span></p></li><li><p><span style=\"color:#9a9da9\">Deep understanding of training and inference bottlenecks—familiar with scaling laws, throughput optimization, and the hardware characteristics that shape them</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Preferred Skills</span></strong></p><ul><li><p><span style=\"color:#9a9da9\">Experience developing or tuning CUDA or Triton kernels with understanding of hardware-level optimization: vectorization, tensor cores, memory hierarchies</span></p></li><li><p><span style=\"color:#9a9da9\">Familiarity with quantization strategies (PTQ, QAT, INT8/FP8) and inference serving systems (TensorRT or equivalent)</span></p></li><li><p><span style=\"color:#9a9da9\">Experience designing data collection and management systems for robotic or physical AI fleets, including annotation tooling, dataset visualization, and automated labeling</span></p></li><li><p><span style=\"color:#9a9da9\">Experience collaborating with external dataset providers or curating large-scale multi-modal pre-training datasets</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Benefits &amp; Compensation</span></strong></p><ul><li><p><span style=\"color:#9a9da9\">Salary Range: $180,000 - $300,000 + Equity</span></p></li><li><p><span style=\"color:#9a9da9\">Health, dental, and vision insurance</span></p></li><li><p><span style=\"color:#9a9da9\">401(k) with company match</span></p></li><li><p><span style=\"color:#9a9da9\">Paid time off and holidays</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Equal Opportunity Employer</span></strong></p><p><span style=\"color:#9a9da9\">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.</span></p><p style=\"min-height: 1.7em;\"></p>",
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      "title": "AI Research Engineer - Infrastructure",
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      "description": "<p><strong><span style=\"color:#9a9da9\">AI Research Engineer - Infrastructure</span></strong></p><p><strong><span style=\"color:#9a9da9\">San Carlos, CA (on-site)</span></strong></p><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">About 1X</span></strong></p><p><span style=\"color:#9a9da9\">We’re building humanoid robots that work in home - doing the chores, handling the tasks, and giving people their time back. Simple, but it’s not.&nbsp;</span></p><p style=\"min-height: 1.7em;\"></p><p><span style=\"color:#9a9da9\">To do this right, we have to solve robotics, AI, manufacturing - at the same time, at scale, in a form factor that has to be safe enough to live with your family. If you’re inspired by this, you’ll thrive here. We’ve been at this since 2014 and we’re at the point where the hard problems are behind us and the hard work is in front of us.&nbsp;<br></span></p><p><span style=\"color:#9a9da9\">NEO is our flagship - a home robot designed to move, learn, and operate in the real world alongside real people. We’re not demoing it - we’re shipping it. We’re excited to meet you, if this excites you.&nbsp;</span></p><p style=\"min-height: 1.7em;\"></p><p><span style=\"color:#9a9da9\">If you’ve spent your career working on problems that matter and want to see them actually reach the world - this is that moment. We’re scaling, we’re hiring with intention, and we need people who want to build something that will genuinely change how humans spend their time - safely creating abundance for all.&nbsp;</span></p><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">About the Team</span></strong></p><p><span style=\"color:#9a9da9\">The 1X World Model Lab is an embodied AI research organization focused on pretraining the foundation models to accelerate the emergence of embodied intelligence.<br></span></p><p><span style=\"color:#9a9da9\">The lab is founded on a simple thesis: </span><strong><em><span style=\"color:#9a9da9\">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.</span></em></strong></p><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Your Charter</span></strong></p><p><span style=\"color:#9a9da9\">Own the infrastructure that enables 1X's AI to improve continuously at scale, spanning the data pipelines that make fleet experience training-ready and the distributed training and inference systems that turn data into capability. This is critical-path work: the speed at which 1X's robots learn is directly determined by how efficiently we collect high-quality data, how reliably we run large training jobs, and how effectively we deploy the resulting models to hardware. Depending on your background and interests, you will focus on data infrastructure, compute scaling, or both.</span></p><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Key Outcomes</span></strong></p><ul><li><p><span style=\"color:#9a9da9\">Build and operate data pipelines that make fleet-collected robot experience consistently queryable, well-labeled, and training-ready, automating ETL across on-robot, on-premise, and cloud infrastructure</span></p></li><li><p><span style=\"color:#9a9da9\">Own distributed training infrastructure that supports GPU runs reliably: fault tolerance, experiment tracking, throughput optimization, and distributed operations at scale</span></p></li><li><p><span style=\"color:#9a9da9\">Optimize inference performance for both datacenter workloads (world models, diffusion engines) and on-device robot policies, using quantization, scheduling, and distillation to reduce latency and improve throughput</span></p></li><li><p><span style=\"color:#9a9da9\">Deliver annotation and dataset tooling: visualization interfaces, labeling automation, ML-based dataset organization that accelerates the data-to-model cycle for the research team</span></p></li><li><p><span style=\"color:#9a9da9\">Ensure compute is never the constraint: design systems where data quality and quantity, not infrastructure bottlenecks, determine the limits of what the models can learn</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Key Competencies</span></strong></p><ul><li><p><strong><span style=\"color:#9a9da9\">Scale-first mindset </span></strong><span style=\"color:#9a9da9\">believes scale is foundational to capable humanoid robotics; designs systems with 10x and 100x growth in mind, and pushes to remove whatever is currently the binding constraint on model improvement</span></p></li><li><p><strong><span style=\"color:#9a9da9\">Full-pipeline thinker </span></strong><span style=\"color:#9a9da9\">understands the path from robot sensor to trained model and can reason about bottlenecks at every layer: data collection, labeling quality, training throughput, and inference latency</span></p></li><li><p><strong><span style=\"color:#9a9da9\">Hands-on optimizer </span></strong><span style=\"color:#9a9da9\">comfortable writing CUDA or Triton kernels, tuning distributed training configurations, or redesigning ETL pipelines, whichever layer needs work</span></p></li><li><p><strong><span style=\"color:#9a9da9\">Production-minded researcher </span></strong><span style=\"color:#9a9da9\">transforms experimental systems into reliable, production-grade platforms; brings engineering rigor to infrastructure that other teams depend on every day</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Benefits &amp; Compensation</span></strong></p><ul><li><p><span style=\"color:#9a9da9\">Salary Range: $180,000 - $300,000 + Equity</span></p></li><li><p><span style=\"color:#9a9da9\">Health, dental, and vision insurance</span></p></li><li><p><span style=\"color:#9a9da9\">401(k) with company match</span></p></li><li><p><span style=\"color:#9a9da9\">Paid time off and holidays</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Equal Opportunity Employer</span></strong></p><p><span style=\"color:#9a9da9\">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.</span></p>",
      "requirements": "<p><strong><span style=\"color:#9a9da9\">Minimum Requirements</span></strong></p><ul><li><p><span style=\"color:#9a9da9\">Strong programming experience in Python and/or C++</span></p></li><li><p><span style=\"color:#9a9da9\">Degree in Computer Science or a related field</span></p></li><li><p><span style=\"color:#9a9da9\">Experience in distributed training frameworks (e.g., TorchTitan, DeepSpeed, FSDP/ZeRO) and/or large-scale data pipeline and ETL systems</span></p></li><li><p><span style=\"color:#9a9da9\">Deep understanding of training and inference bottlenecks—familiar with scaling laws, throughput optimization, and the hardware characteristics that shape them</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Preferred Skills</span></strong></p><ul><li><p><span style=\"color:#9a9da9\">Experience developing or tuning CUDA or Triton kernels with understanding of hardware-level optimization: vectorization, tensor cores, memory hierarchies</span></p></li><li><p><span style=\"color:#9a9da9\">Familiarity with quantization strategies (PTQ, QAT, INT8/FP8) and inference serving systems (TensorRT or equivalent)</span></p></li><li><p><span style=\"color:#9a9da9\">Experience designing data collection and management systems for robotic or physical AI fleets, including annotation tooling, dataset visualization, and automated labeling</span></p></li><li><p><span style=\"color:#9a9da9\">Experience collaborating with external dataset providers or curating large-scale multi-modal pre-training datasets</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Benefits &amp; Compensation</span></strong></p><ul><li><p><span style=\"color:#9a9da9\">Salary Range: $180,000 - $300,000 + Equity</span></p></li><li><p><span style=\"color:#9a9da9\">Health, dental, and vision insurance</span></p></li><li><p><span style=\"color:#9a9da9\">401(k) with company match</span></p></li><li><p><span style=\"color:#9a9da9\">Paid time off and holidays</span></p></li></ul><p style=\"min-height: 1.7em;\"></p><p><strong><span style=\"color:#9a9da9\">Equal Opportunity Employer</span></strong></p><p><span style=\"color:#9a9da9\">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.</span></p><p style=\"min-height: 1.7em;\"></p>",
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