ML Engineer | Remote

Crossing Hurdles; United States; On-site; USD 120,000 - 170,000; Full time

Job summary

Crossing Hurdles is seeking a highly skilled machine learning researcher/engineer to develop and validate ML models, training pipelines, and inference systems. The role focuses on building robust data pipelines, evaluation frameworks, and numerical methods within a scalable infra environment.

Ideal candidates hold a Master’s or PhD in a quantitative field, have strong ML experience, and demonstrate Python proficiency, with a track record from a technology company, AI lab, or academic setting.

Qualifications

• Master's degree or PhD in CS, ML, AI, applied math, statistics, engineering, or related quantitative field.
• Strong relevant experience in machine learning is required.
• Proficiency with Python and coding concepts/tools is expected.
• Experience at a well-established tech company, AI lab, or research org is preferred.
• Exceptional open-source or academic experience may qualify.

Responsibilities

• Develop and validate ML models, training pipelines, inference systems, and supporting infra.
• Implement model components, data pipelines, evaluation systems, and numerical methods.
• Build reproducible programmatic workflows using Python and CLI tools.
• Optimize memory/throughput and debug numerical or system-level failures.
• Verify implementations meet accuracy and performance requirements.

Skills

Machine learning

Open-source experience

Research experience

Python programming

Education

Master's or PhD in CS/ML/AI/Applied Math/Statistics/Engineering

Tools

Python

Job description

• 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 memory or throughput and debug numerical or system-level failures.
• Verify that implementations satisfy objective correctness and performance requirements.

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 relevant experience in machine learning.
• Practical proficiency with Python and coding agents.
• Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering environment is strongly preferred.
• Exceptional open-source or academic experience may also qualify.