Remote ML Platform Engineer (Contract)

Crossing Hurdles; United States; Remote; USD 138,000 - 207,000; Part time

Job summary

Crossing Hurdles is seeking an ML Engineer for a remote contract role. You will develop and validate machine-learning models, training pipelines, and inference systems while building robust infrastructure and reproducible workflows using Python and command-line tools.

The position emphasizes optimizing latency, throughput, memory usage, and hardware utilization, with a focus on diagnosing numerical instability and distributed-system issues. 10–40 hours per week, remote work arrangement.

Qualifications

• Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or closely related quantitative discipline.
• Strong professional or research experience in machine learning.
• Practical proficiency with Python.
• Meaningful experience with at least two ML frameworks, libraries, or inference tools.
• Ability to debug ML systems beyond surface-level API usage.

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.

Skills

Python scripting

ML system debugging

Performance optimization

Distributed systems

Education

Master's degree or PhD in CS/ML/AI/Applied Math/Stats

Tools

TensorFlow

PyTorch

Job description

Crossing Hurdles is seeking an ML Engineer for a remote contract role. You will develop and validate machine-learning models, training pipelines, and inference systems while building robust infrastructure and reproducible workflows using Python and command-line tools.

The position emphasizes optimizing latency, throughput, memory usage, and hardware utilization, with a focus on diagnosing numerical instability and distributed-system issues. 10–40 hours per week, remote work arrangement.