Machine Learning Research – Engineering Specialist

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Develop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure.

• Implement or modify model components, data pipelines, evaluation systems, and numerical methods utilizing Python.

• Create reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks.

• Troubleshoot numerical, algorithmic, and system-level failures to pinpoint root causes and apply dependable solutions.

• Enhance model training and inference for memory utilization, computational efficiency, throughput, and overall performance.

• Design and carry out tests to ensure implementation accuracy and adherence to performance requirements.

• Review and assess complex machine learning engineering tasks, including existing code and proposed solutions.

• Utilize coding agents as part of the development process to expedite implementation, debugging, testing, and code reviews while validating generated results.

• Clearly document technical methodologies, implementation choices, test outcomes, and performance insights.

• Provide high-quality, reproducible task submissions within project timelines.

⛳️ Requirements

• Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative field.

• Significant professional or research experience in machine learning and practical ML engineering.

• Proficient Python programming skills, including the capacity to implement, debug, test, and optimize complex code.

• Practical experience with coding agents within a Python development environment.

• Knowledge of machine learning model development, training and inference workflows, and evaluation methods.

• Ability to construct reproducible implementations and validate accuracy through systematic testing.

• Strong quantitative reasoning and problem-solving abilities, especially in diagnosing numerical or computational challenges.

• Capability to work independently, manage technical tasks, and meet established quality and submission standards.

• Excellent written communication skills with the ability to articulate technical findings effectively.

• Willingness to contribute approximately 15 hours per week and commence the first task within 24–48 hours after onboarding.

🏝️ Benefits

• Flexible working hours and the opportunity for remote work.

• Engaging and collaborative team environment.

• Opportunities for professional development and skill enhancement.

• Contribution to innovative projects in the field of machine learning and artificial intelligence.