Machine Learning Research & Engineering Specialist
About The Position
Gramian Consultancy is seeking a highly skilled Machine Learning Research & Engineering Specialist for an advanced AI training project focused on model development, training and inference systems, numerical computing, and performance optimization. This coding-intensive role involves hands-on Python development, machine learning engineering, and use of coding agents within development workflows. The specialist will build, modify, debug, and validate machine learning implementations; create reproducible training and inference pipelines; and optimize systems for correctness, memory usage, and throughput. The role is intended for an experienced or research-level engineer with strong quantitative foundations and practical skills in solving complex machine learning engineering problems. The position is remote worldwide. Candidates should have strong written and verbal English. The expected contribution is approximately 15 hours per week, with the first task beginning within 24–48 hours after onboarding.
Requirements
- Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.
- Strong professional or research experience in machine learning and practical ML engineering.
- Strong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code.
- Hands-on experience using coding agents within a Python development workflow.
- Understanding of machine learning model development, training and inference workflows, and evaluation methods.
- Ability to build reproducible implementations and verify correctness through systematic testing.
- Strong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues.
- Ability to work independently, manage technical tasks, and meet defined quality and submission requirements.
- Strong written communication skills and ability to explain technical findings.
- Strong written and verbal English.
- Availability to contribute approximately 15 hours per week and begin the first task within 24–48 hours after onboarding.
Responsibilities
- 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 using Python.
- Build reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks.
- Debug numerical, algorithmic, and system-level failures, identify root causes, and implement reliable solutions.
- Optimize model training and inference for memory usage, computational efficiency, throughput, and performance.
- Design and execute tests to verify implementation correctness and compliance with objective performance requirements.
- Review and validate challenging machine learning engineering tasks, including existing code and proposed solutions.
- Use coding agents in development workflows to accelerate implementation, debugging, testing, and code review, while validating generated results.
- Document technical approaches, implementation decisions, test results, and performance findings clearly.
- Deliver high-quality, reproducible task submissions within project deadlines.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
