AI Systems Engineer - ML Pipelines & Validation

Crossing Hurdles; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Crossing Hurdles seeks a skilled ML engineer to develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.

You will implement model components, data pipelines, evaluation systems, and numerical methods, building reproducible workflows with Python and command-line tools. You will optimize memory and throughput and debug numerical or system-level failures to meet performance goals.

Qualifications

• Master’s degree or PhD in Computer Science, ML, AI, Applied Mathematics, Statistics, Engineering, or closely related quantitative discipline.
• Strong relevant experience in machine learning.
• 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.

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

Skills

Machine learning experience

Python proficiency

Agent programming

Open-source experience

Academic research

Education

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

Job description

Crossing Hurdles seeks a skilled ML engineer to develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.

You will implement model components, data pipelines, evaluation systems, and numerical methods, building reproducible workflows with Python and command-line tools. You will optimize memory and throughput and debug numerical or system-level failures to meet performance goals.