Machine Learning Research & Engineering Specialist

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

📋 Description

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

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

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

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

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

• Design and conduct tests to ensure the accuracy of implementations and adherence to performance objectives.

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

• Utilize coding agents within the development process to expedite implementation, debugging, testing, and code review while validating the results generated.

• 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 closely related quantitative field.

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

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

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

• In-depth understanding of machine learning model development, training and inference workflows, and evaluation techniques.

• Ability to create reproducible implementations and verify accuracy through systematic testing.

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

• Capacity to work independently, manage technical responsibilities, and fulfill defined quality and submission standards.

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

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

🏝️ Benefits

• Opportunity to work on cutting-edge machine learning projects.

• Flexible working hours and remote work options.

• Access to professional development resources and training.