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Machine Learning Ops Engineer | Remote | $90 -$140/hr

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  • US
    New York, New York, United States
  • US
    New York, New York, United States

Über

About The Role This role focuses on advancing next-generation AI systems through large-scale ML infrastructure, training optimization, and framework-level engineering. The work involves supporting cutting‑edge GenAI initiatives, improving model performance, and contributing to highly scalable AI training environments.
Position: MLOps Engineer
Type: W2 | Full-Time Contingent Role
Engagement: Remnote Global | Full-time
Compensation: $90–$140/hour
Location: United States (Remote)
Role Responsibilities
Support AI research and engineering teams in improving ML infrastructure and training systems
Design advanced MLOps and ML systems tasks with accurate, structured technical solutions
Evaluate ML systems outputs and provide detailed technical feedback
Develop evaluation rubrics and frameworks for distributed systems, training pipelines, and kernel‑level optimization
Collaborate with domain experts to maintain consistency and quality across AI training workflows
Contribute to improvements in large-scale model training performance and infrastructure reliability
Requirements
2 years of professional experience in ML infrastructure, MLOps, or ML systems engineering
Hands‑on production experience with JAX and/or PyTorch at scale
Experience writing or optimizing GPU kernels using Pallas or Triton
Strong understanding of ML training systems and distributed infrastructure
Demonstrated career progression in engineering or AI infrastructure roles
Ability to commit to a full‑time 40‑hour/week weekday schedule
Strong written communication and technical documentation skills
Engagement Details
W2 employment engagement
Full-time, 40 hours/week
No conflicting full-time engagements permitted
Remote role within the United States
Opportunity to contribute to leading frontier AI initiatives
Application & Onboarding Process
Upload resume
AI interview: A short, 15‑minute conversational session to assess background and technical expertise
Follow‑up communication with next steps and onboarding details
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  • New York, New York, United States

Sprachkenntnisse

  • English
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