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Machine Learning Engineer | Remote

Remote / Online - Candidates ideally in
Washington, District of Columbia, 20022, USA
Listing for: Crossing Hurdles
Remote/Work from Home position
Listed on 2026-09-25
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Python, Data Scientist
Salary/Wage Range or Industry Benchmark: 100 - 150 USD Hourly USD 100.00 150.00 HOUR
Job Description & How to Apply Below
  • Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
  • Implement model components, data pipelines, evaluation systems, and numerical methods.
  • Build reproducible programmatic workflows using Python and command-line tools.
  • Optimize training or inference for latency, throughput, memory usage, and hardware utilization.
  • Diagnose numerical instability, incorrect tensor behavior, memory bottlenecks, distributed-system failures, and performance regressions.

Position: ML Engineer

Type: Contract

Compensation: $100 - $150/hour

Location: Remote

Commitment: 10-40 hrs/week

Role Responsibilities
  • Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
  • Implement model components, data pipelines, evaluation systems, and numerical methods.
  • Build reproducible programmatic workflows using Python and command-line tools.
  • Optimize training or inference for latency, throughput, memory usage, and hardware utilization.
  • Diagnose numerical instability, incorrect tensor behavior, memory bottlenecks, distributed-system failures, and performance regressions.
Requirements
  • A master s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.
  • Strong professional or research experience in machine learning.
  • Practical proficiency with Python.
  • Meaningful experience with at least two relevant ML frameworks, libraries, or inference tools.
  • Ability to debug ML systems beyond surface-level API usage.
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