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

$1.8M
per year
Full-time Remote Last verified 21 Jul 2026
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About the Role

The Role In this role, you will take technical ownership of the distributed systems and platforms that enable researchers to train increasingly capable models, execute large-scale experiments, and deploy specialized AI systems efficiently. You will work across distributed training, GPU infrastructure, inference optimization, simulation environments, and agent execution frameworks, making critical architectural decisions that directly influence research velocity and model performance.

What You'll Do

  • Architect, build, and scale shared infrastructure for supervised fine-tuning (SFT), reinforcement learning (RL), and on-policy distillation (OPD), supporting language, multimodal, and robotics workloads.
  • Design distributed training and execution pipelines that coordinate GPU workers, rollout generation, teacher-model inference, reward computation, and simulation environments.
  • Develop high-performance infrastructure for model training and inference, optimizing GPU utilization, memory management, communication, storage, and distributed execution.
  • Build and evolve the core architecture of micro1's agent ecosystem, including execution runtimes, tool interfaces, environment integrations, model registries, and serving APIs.
  • Develop robust systems for experiment tracking, dataset and model versioning, checkpointing, fault recovery, and observability to improve research reproducibility and operational reliability.
  • Identify and eliminate infrastructure bottlenecks, reducing experiment turnaround time and enabling researchers to run increasingly complex training workloads.
  • Define technical standards, platform interfaces, and architectural patterns that support collaboration across research, infrastructure, and applied engineering teams.
  • Lead critical engineering initiatives from system design through implementation and production operations, mentoring engineers while maintaining direct ownership of technically challenging components.

You're a Good Fit If You

  • Required skills: Distributed ML Training Infrastructure, GPU Performance & Inference Optimization, Distributed Systems & Platform Architecture, Technical Leadership & System Ownership

Role Highlights

Pay
$600K-$1.8M/yr
Contract
Full-time
Location
Remote
Category
Coding
Posted
5 days ago
Job ID

Pay & Payout

Engaged directly through micro1. Apply via the link below - micro1 handles onboarding and payment.

Common Questions

micro1 has a reliability rating of reliable based on the listings we track, with an onboarding time of 1-3 days. See our full micro1 review for the details behind that rating.

Applying takes you to micro1's own website, where the application is completed. We are not a recruiter or employer and do not process applications directly - we may be recorded as the referring source.

$600K-$1.8M/yr - Engaged directly through micro1. Apply via the link below - micro1 handles onboarding and payment.

Architect, build, and scale shared infrastructure for supervised fine-tuning (SFT), reinforcement learning (RL), and on-policy distillation (OPD), supporting language, multimodal, and robotics workloads. Design distributed training and execution pipelines that coordinate GPU workers, rollout generation, teacher-model inference, reward computation, and simulation environments. Develop high-performance infrastructure for model training and inference, optimizing GPU utilization, memory management, communication, storage, and distributed execution.

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About micro1 for this role

We track 368 open micro1 roles on AI Work Expert. This role lists $600K-$1.8M/yr. Our reliability rating for micro1 is reliable, with an onboarding time of 1-3 days.