Machine Learning Engineer | Remote

Crossing Hurdles; Netherlands; Remoto; EUR 74.000 - 148.000; Tempo pieno

Descrizione del lavoro

Crossing Hurdles is seeking an ML Engineer for a remote contract role. You will develop and validate ML models, training pipelines, inference systems, and supporting infrastructure, with a focus on scalable, reproducible workflows.

Requirements include a Master’s degree or PhD in a quantitative field, strong ML experience, Python proficiency, and experience at notable tech or research environments.

Competenze

• Master's degree or PhD in CS, ML, AI, or related quantitative field.
• Strong experience in machine learning.
• Proficiency with Python and coding tools.
• Experience at a tech company, AI lab, or research org preferred.

Mansioni

• 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.

Conoscenze

Strong ML experience

Python proficiency

Numerical methods

Formazione

Master's degree or PhD in CS/ML/AI

Strumenti

Python

Descrizione del lavoro

• 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.

Position: ML Engineer

Type: Contract

Compensation: $60 - $120/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 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.