Machine Learning Research – Engineering Specialist

This is a fully remote position, open to applicants in United States, +5 more countries.

📋 Description

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

• Modify or create model components, data pipelines, evaluation systems, and numerical methods utilizing Python.

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

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

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

• Design and carry out tests to confirm implementation accuracy and adherence to specified performance criteria.

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

• Utilize coding agents as part of the development workflow to expedite implementation, debugging, testing, and code review while validating generated outcomes.

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

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

⛳️ Requirements

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

• Significant professional or research experience in machine learning along with practical ML engineering skills.

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

• Practical experience using coding agents within a Python development workflow.

• Knowledge of machine learning model development, including training and inference workflows, as well as evaluation techniques.

• Capability to create reproducible implementations and validate correctness through systematic testing.

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

• Ability to work autonomously, manage technical tasks, and adhere to defined quality and submission standards.

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

• Availability to commit approximately 15 hours per week and to commence the first task within 24–48 hours post-onboarding.

🏝️ Benefits

• Engage in cutting-edge machine learning projects.

• Collaborate with a team of skilled professionals in a dynamic environment.

• Flexible working hours to accommodate your schedule.

• Opportunities for professional growth and skill enhancement.