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MLOps Engineer (JAX, PyTorch, Pallas/Triton)

3 weeks, 5 days ago
United States
Contract
Junior
Machine Learning Engineer
Software Development
MLOps PyTorch
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Weekday

Weekday helps companies hire engineers who are vouched by other software engineers, enabling passive income for engineers. They offer services like drafting outreach messages, shortlisting candidates, and conducting reference checks. Backed by Y Combin...

Construction & Engineering
11-50
Founded 2020
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Description

  • Partner with research and engineering teams to improve AI model capabilities in MLOps, ML infrastructure, and large-scale training systems.
  • Design challenging, real-world MLOps and machine learning systems tasks that reflect production engineering scenarios.
  • Develop accurate, well-documented solutions to complex ML infrastructure and training pipeline problems.
  • Review and evaluate technical tasks and AI-generated solutions, providing clear and actionable written feedback.
  • Create evaluation rubrics and scoring frameworks for distributed training, ML pipeline design, infrastructure optimization, kernel-level programming, and performance tuning.
  • Collaborate with subject matter experts to maintain consistency, quality, and technical accuracy across training datasets.
  • Contribute domain expertise to improve the reasoning capabilities of advanced AI systems.

Requirements

  • Minimum 2 years of professional experience in MLOps, Machine Learning Infrastructure, or ML Systems Engineering within a recognized technology organization.
  • Hands-on production experience with JAX and/or PyTorch in large-scale machine learning environments.
  • Practical experience developing or optimizing custom GPU kernels using Pallas (JAX) or Triton.
  • Strong understanding of distributed training systems, model optimization, and scalable ML infrastructure.
  • Demonstrated career growth and increasing technical responsibility.
  • Availability to work 40 hours per week during standard weekday business hours.
  • Excellent written communication skills with the ability to clearly explain technical concepts and architectural decisions.
  • Experience designing and optimizing large-scale ML training pipelines (preferred).
  • Knowledge of distributed computing and GPU performance optimization (preferred).
  • Familiarity with evaluation methodologies for AI models and ML systems (preferred).
  • Experience collaborating with research teams on advanced machine learning projects (preferred).
  • Passion for advancing AI infrastructure and frontier model development (preferred).
  • H-1B sponsorship and STEM OPT candidates are not eligible for this opportunity.

Benefits

  • Compensation of $70-$110 per hour.
  • Fully remote engagement.
  • Independent contractor arrangement.
  • Weekly payments via Stripe or Wise.
  • Potential for project extension based on requirements and performance.

Interested in this position?

Apply directly on the company website

Apply Now

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