Machine Learning Engineer
Keystone Recruitment
Job Overview
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Job Description
Machine Learning Engineer
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 Machine Learning 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
Key skills/competency
- Machine Learning
- AI Systems
- ML Engineering
- Applied Research
- Model Evaluation
- System Design
- Experimentation
- Debugging
- Optimization
- Technical Writing
How to Get Hired at Keystone Recruitment
- Research Keystone Recruitment's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight ML engineering and applied research experience, focusing on model evaluation and system design.
- Showcase project expertise: Provide a portfolio or detailed examples of relevant ML project work and contributions.
- Prepare for technical deep dives: Expect questions on ML system design, optimization tradeoffs, and evaluation methodologies.
- Emphasize communication skills: Practice articulating complex technical concepts clearly, as written assessments are crucial.
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