Senior ML Research & Engineering Specialist (Remote)

Gramian Consulting Group; Oregon; Hybrid; USD 120,000 - 190,000; Part time

Job summary

GramianGramian Consultancy seeks a highly skilled Machine Learning Research & Engineering Specialist for an advanced AI training project. You will develop, train, and optimize ML models and inference systems, with a strong emphasis on Python-based pipelines and reproducible workflows.

The role is experienced/research-level, remote worldwide, ~15 hours per week, and requires a Master’s or PhD in a quantitative field.

Qualifications

• Master's degree or PhD in Computer Science, ML, AI, applied mathematics, statistics, or a closely related field.
• Experience in ML engineering and practical ML development is required.
• Strong Python programming and debugging skills with non-trivial code.

Responsibilities

• Develop, validate, and optimize ML models, training pipelines, and inference systems.
• Implement model components, data pipelines, evaluation systems, and numerical methods in Python.
• Build reproducible workflows and test suites using Python and ML frameworks.
• Debug numerical, algorithmic, and system-level failures and identify root causes.
• Optimize training and inference for memory, speed, and throughput; document results.
• Review code and MC tasks; validate solutions and support the project deadlines.
• Use coding agents in the development workflow to accelerate implementation and review.

Skills

Machine learning

Python programming

Debugging

Numerical computing

Performance optimization

Independent work

English communication

Education

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

Tools

Python

ML frameworks

Command-line tools

Job description

GramianGramian Consultancy seeks a highly skilled Machine Learning Research & Engineering Specialist for an advanced AI training project. You will develop, train, and optimize ML models and inference systems, with a strong emphasis on Python-based pipelines and reproducible workflows.

The role is experienced/research-level, remote worldwide, ~15 hours per week, and requires a Master’s or PhD in a quantitative field.