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PyTorch & MLOps AI Specialist

22 hours, 39 minutes ago
United States
Full-time
Junior
Machine Learning Engineer
DevOps and Infrastructure
Generative AI LLM MLOps PyTorch
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Weekday

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
View All Jobs 134

Description

  • Partner with research and engineering teams to identify and address gaps in MLOps, machine learning infrastructure, and model training systems.
  • Design challenging, real-world tasks focused on distributed training, ML frameworks, model optimization, and infrastructure engineering.
  • Develop accurate, well-structured solutions to complex MLOps and ML systems problems.
  • Evaluate technical tasks and solutions and provide detailed, actionable feedback.
  • Create evaluation frameworks and scoring rubrics for training pipeline architecture, distributed systems reasoning, performance optimization, and kernel-level programming.
  • Contribute domain expertise to improve AI model capabilities in machine learning engineering topics.
  • Collaborate with subject matter experts to ensure consistency, quality, and technical accuracy across datasets and evaluations.

Requirements

  • 2+ years of professional experience in ML Infrastructure, MLOps, ML Systems Engineering, or a closely related field.
  • Strong hands-on experience building and operating production-scale machine learning systems.
  • Advanced proficiency with PyTorch, including model training, optimization, and deployment workflows.
  • Experience developing, tuning, or optimizing custom GPU kernels using Triton, Pallas, or similar frameworks.
  • Demonstrated career growth and increasing technical responsibility.
  • Ability to commit to a full-time, 40-hour-per-week schedule during standard business days.
  • Excellent written communication skills and the ability to clearly explain complex technical concepts and engineering decisions.
  • Experience with large-scale distributed training frameworks and infrastructure (preferred).
  • Knowledge of GPU performance optimization and compiler-level ML tooling (preferred).
  • Familiarity with modern AI training pipelines, model evaluation methodologies, and LLM development workflows (preferred).
  • Experience mentoring engineers or contributing to technical standards and best practices (preferred).
  • Background in cloud-native ML infrastructure and production deployment environments (preferred).

Benefits

  • Compensation of $70-$110 per hour.
  • Full-time, 40-hour-per-week engagement.
  • Opportunity to work alongside leading AI researchers and engineers on frontier AI systems.
  • Chance to influence the development and evaluation of next-generation large language models.
  • High-impact work at the forefront of AI innovation.
  • Reasonable accommodations available upon request.

Interested in this position?

Apply directly on the company website

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