Member of Technical Staff, Model Training (infra & platform)

Role: Model Training Member of Technical Staff (infra & platform)

Type of job: full-time

Location: Remote

About the role

You'll own, technically, the distributed systems and platforms that let researchers train ever more capable models, run large experiments, and ship specialized AI systems efficiently.

Your work spans distributed training, GPU infrastructure, inference tuning, simulation environments, and agent execution frameworks, with key architecture choices that shape research speed and model performance.

What You'll Do

• Design, build, and scale shared infrastructure for SFT (supervised fine-tuning), OPD (on-policy distillation), and RL (reinforcement learning) across robotics, multimodal, and language workloads.
• Design pipelines for distributed training and execution that coordinate rollout generation, GPU workers, reward computation, inference from teacher models, and simulation environments.
• Build fast infrastructure for training and inference, tuning GPU use, memory handling, communication, storage, and distributed execution.
• Build out and evolve the core design of micro1's agent ecosystem: model registries, serving APIs, tool interfaces, execution runtimes, and environment integrations.
• Build sturdy systems for tracking experiments, versioning datasets and models, checkpointing, recovering from faults, and observability, so research is reproducible and operations dependable.
• Find and remove infrastructure bottlenecks so experiments finish sooner and researchers can run ever more complex training jobs.
• Set platform interfaces, technical standards, and architecture patterns that help research, infrastructure, and applied engineering teams work together.
• Lead key engineering projects from system design to build and production, coaching engineers while personally owning the hardest technical pieces.

What We're Looking For

• Strong CS fundamentals, especially concurrency, networking, distributed systems, and performance engineering.
• Broad experience designing, building, and running distributed compute platforms or backend systems that scale.
• Skill in Python plus at least one systems language like C++, Rust, or Go.
• Practical work with distributed training, model inference, GPU-based ML infrastructure, or orchestrating compute at large scale.
• Solid grasp of system performance: memory efficiency, compute use, scheduling, communication overhead, and fault tolerance.
• Background designing dependable APIs, services, and infrastructure parts for complicated engineering or research workflows.
• Shown technical ownership: making architecture calls, leading projects across teams, and shipping systems other engineers rely on.
• Works well in fast research settings where needs shift and infrastructure has to support quick experimentation.

Nice to Have

• Background with distributed ML tools like DeepSpeed, Ray, Megatron-LM, PyTorch Distributed, or comparable systems.
• Knowledge of GPU inference engines and tuning frameworks like vLLM, TensorRT-LLM, or equivalents.
• Background building RL infrastructure, rollout orchestration, or distributed environments where agents run.
• Knowledge of NCCL, CUDA, GPU kernel tuning, or low-level GPU performance work.
• Background with cluster scheduling, Kubernetes, orchestrating containers, and GPU infrastructure in the cloud.
• Knowledge of robotics infrastructure, simulation platforms, or large systems for evaluating agents.
• Contributions to open-source distributed computing frameworks, infrastructure, or fast ML systems.

Compensation & Benefits Notice

Nationally, base pay for this full-time job runs $200,000–$320,000. Every employee can receive equity, and bonuses tied to performance may also apply depending on the role and company policy. Benefits cover health-insurance premiums (reimbursed at up to 100%), paid time off, a 401(k) with a company match, and other perks meant for a remote-first team that performs at a high level.

micro1 hires on an equal-opportunity basis. Every qualified applicant is considered without regard to age, color, disability, national origin, race, religion, sex (pregnancy, gender identity, and sexual orientation included), veteran status, genetic information, or any other trait that applicable local laws, ordinances, or regulations protect. Applicants who need help or a reasonable accommodation while applying can ask for it.

AI tools help screen and assess candidates in the hiring process. They are meant to support people's hiring decisions, not to take them over.

Application process

Submit your application through NorthStar. Employer screening may follow after submission.