1x.tech
About 1X
We’re an AI and robotics company based in Palo Alto, California, on a mission to build a truly abundant society through general‑purpose robots capable of performing any kind of work autonomously.
We believe that to truly understand the world and grow in intelligence, humanoid robots must live and learn alongside us. That’s why we’re focused on developing friendly home robots designed to integrate seamlessly into everyday life.
We’re looking for curious, driven, and passionate people who want to help shape the future of robotics and AI. If this mission excites you, we’d be thrilled to hear from you and explore how you might contribute to our journey.
Role Overview As a Research Engineer, Scaling, you will design and build infrastructure to support training, evaluation, and deployment at scale across 1X’s fleet of robots. You will take experimental and prototype systems, and transform them into production‑grade systems capable of large‑scale training runs, reliable inference, and efficient edge deployment. Your work will directly impact throughput, latency, and model performance across both data center and on‑device environments.
Responsibilities Own and lead scaling of both distributed training and inference systems
Ensure compute resources are sufficient so that data, not hardware, is the limiter
Enable massive training at scale (1000+ GPUs) on robot data, handling fault tolerance, experiment tracking, distributed operations, and large datasets
Optimize inference throughput in datacenter contexts (e.g. for world models and diffusion engines)
Reduce latency and optimize performance for on‑device robot policies through techniques like quantization, scheduling, distillation, etc.
Strong programming experience in Python and/or C++
Deep intuitive understanding of what affects training or inference speed: from bottlenecks to scaling laws
A mindset aligned with extremely high scaling: belief that scale is foundational to enabling humanoid robotics
Ideal Experiences Degree in Computer Science or a related field
Hands‑on experience with distributed training frameworks (e.g. TorchTitan, DeepSpeed, FSDP/ZeRO), multi‑node debugging, experiment management
Proven skills optimizing inference performance: graph compilers, batching/scheduling, serving systems (e.g., using TensorRT or equivalents)
Familiarity with quantization strategies: PTQ, QAT, INT8/FP8; tools like TensorRT, bitsandbytes, etc.
Experience writing or tuning CUDA or Triton kernels; understanding of hardware features like vectorization, tensor cores, and memory hierarchies
Benefits & Compensation Salary Range: $180,000 – $300,000
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.
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Role Overview As a Research Engineer, Scaling, you will design and build infrastructure to support training, evaluation, and deployment at scale across 1X’s fleet of robots. You will take experimental and prototype systems, and transform them into production‑grade systems capable of large‑scale training runs, reliable inference, and efficient edge deployment. Your work will directly impact throughput, latency, and model performance across both data center and on‑device environments.
Responsibilities Own and lead scaling of both distributed training and inference systems
Ensure compute resources are sufficient so that data, not hardware, is the limiter
Enable massive training at scale (1000+ GPUs) on robot data, handling fault tolerance, experiment tracking, distributed operations, and large datasets
Optimize inference throughput in datacenter contexts (e.g. for world models and diffusion engines)
Reduce latency and optimize performance for on‑device robot policies through techniques like quantization, scheduling, distillation, etc.
Strong programming experience in Python and/or C++
Deep intuitive understanding of what affects training or inference speed: from bottlenecks to scaling laws
A mindset aligned with extremely high scaling: belief that scale is foundational to enabling humanoid robotics
Ideal Experiences Degree in Computer Science or a related field
Hands‑on experience with distributed training frameworks (e.g. TorchTitan, DeepSpeed, FSDP/ZeRO), multi‑node debugging, experiment management
Proven skills optimizing inference performance: graph compilers, batching/scheduling, serving systems (e.g., using TensorRT or equivalents)
Familiarity with quantization strategies: PTQ, QAT, INT8/FP8; tools like TensorRT, bitsandbytes, etc.
Experience writing or tuning CUDA or Triton kernels; understanding of hardware features like vectorization, tensor cores, and memory hierarchies
Benefits & Compensation Salary Range: $180,000 – $300,000
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.
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