Machine Learning Engineer
Keystone Recruitment
Job Overview
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Job Description
Machine Learning Engineer
Role Overview
One of Keystone Recruitment's clients is seeking an experienced Machine Learning Engineer to evaluate advanced machine learning systems for a leading AI research initiative. This project-based, hourly contract position 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 thrive on deep technical reasoning, experimentation, and system-level thinking. You will directly contribute to how cutting-edge AI systems are evaluated on practical machine learning engineering tasks, shaping the future of AI assessment.
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.
Key skills/competency
- Machine Learning Engineering
- AI Research Evaluation
- Benchmark Design
- ML System Design
- Model Optimization
- Experimentation
- Debugging ML Models
- Technical Assessment
- Applied ML Research
- Written Communication
How to Get Hired at Keystone Recruitment
- Research Keystone Recruitment's client focus: Understand their specialization in advanced AI research and ML engineering roles for contract placements.
- Tailor your resume for ML evaluation: Highlight experience in designing benchmarks, evaluating AI models, and analyzing system performance.
- Showcase practical ML projects: Emphasize hands-on experience with model development, debugging, optimization, and experimentation.
- Prepare for in-depth technical discussions: Be ready to discuss ML system design choices, tradeoffs, and performance implications.
- Demonstrate strong written communication: Practice articulating complex technical concepts clearly, as precise written assessments are key.
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