ML Systems Engineer: Pipelines, Inference & Optimization

Crossing Hurdles; United States; Remote; CAD 110,000 - 150,000; Full time

Job summary

Crossing Hurdles seeks a skilled ML researcher/engineer to craft and validate machine-learning models, training pipelines, and inference systems within a research-driven setting.

You will implement model components, data pipelines, and evaluation systems, building reproducible workflows with Python and CLI tools while optimizing memory and throughput and diagnosing complex failures. Collaboration with a fast-paced team and stakeholders is expected.

Qualifications

• Master's degree or PhD in CS/ML/AI/Applied Math/Statistics/Engineering or related quantitative field.
• Strong experience in machine learning.
• Proficiency with Python and coding agents.
• Experience at a tech company, AI lab, or research organization is preferred.
• Open source or academic experience may 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

Python

Data Pipelines

Command-line

Numerical Methods

Education

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

Tools

Git

Jupyter

Linux

Job description

Crossing Hurdles seeks a skilled ML researcher/engineer to craft and validate machine-learning models, training pipelines, and inference systems within a research-driven setting.

You will implement model components, data pipelines, and evaluation systems, building reproducible workflows with Python and CLI tools while optimizing memory and throughput and diagnosing complex failures. Collaboration with a fast-paced team and stakeholders is expected.