Senior Machine Learning Engineer

Remote
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AI Summary

Transform real-world ML engineering workflows into structured evaluation benchmarks for frontier AI models. Design and write detailed evaluation suites for real-world machine learning engineering tasks. Evaluate AI-generated solutions related to model training, debugging, optimization, and experimentation.

Key Highlights
Transform real-world ML engineering workflows
Design and write detailed evaluation suites
Evaluate AI-generated solutions
Key Responsibilities
Design and write detailed evaluation suites for real-world machine learning engineering tasks
Translate applied ML research and engineering workflows into structured benchmarks
Reason about ML system design choices, tradeoffs, and performance implications
Technical Skills Required
Machine Learning Model Development Experimentation Evaluation ML System Design Optimization
Benefits & Perks
$100-$120 per hour
Fully remote
Asynchronous work
Weekly payments via Stripe or Wise
Independent contractor classification

Job Description


  • Title: Machine Learning Engineer
  • Employment Type: Hourly Contract
  • Location: Remote
  • Compensation: $100–$120 per hour


Role

One of our clients is hiring a Machine Learning Engineer to support the evaluation of advanced machine learning systems for a leading AI research initiative. This project-based role focuses on transforming real-world ML engineering workflows into structured evaluation benchmarks for frontier AI models.


About the Role

This position is ideal for experienced ML engineers or applied researchers who enjoy deep technical reasoning, experimentation, and system-level thinking. You will contribute directly to how cutting-edge AI systems are evaluated on practical machine learning engineering tasks.


Key Responsibilities

  • Design and write detailed evaluation suites for real-world machine learning engineering tasks
  • Translate applied ML research and engineering workflows into structured benchmarks
  • Evaluate AI-generated solutions related to model training, debugging, optimization, and experimentation
  • Reason about ML system design choices, tradeoffs, and performance implications
  • Produce clear, technically precise written assessments


Ideal Qualifications

  • 3+ years of experience in machine learning engineering or applied ML research
  • Hands-on experience with model development, experimentation, and evaluation
  • Background in ML research within an industry lab or academic setting (strongly preferred)
  • Strong understanding of ML system design and optimization tradeoffs
  • Excellent written communication skills and high attention to technical detail


More About the Opportunity

  • Fully remote, asynchronous work completed on your own schedule
  • Project-based engagement with potential extensions based on performance and project needs
  • Weekly payments via Stripe or Wise
  • Independent contractor classification
  • No access to confidential or proprietary employer or client data


Apply Now


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