Remote Senior ML Research & Engineering Specialist

Gramian Consulting Group; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Gramian Consultancy seeks an experienced Machine Learning Research & Engineering Specialist for an advanced AI training project. You will develop, train, and optimize ML models, inference systems, and numerical methods in Python, with a focus on reproducible pipelines and robust engineering practices.

You will work on challenging ML tasks, validate results, and use coding agents within a Python workflow to accelerate development.

Qualifications

• Master’s degree or PhD in a quantitative discipline.
• Strong Python programming skills and ML engineering experience.
• Hands-on experience with coding agents in Python workflows.
• Ability to debug, test, and optimize ML code and pipelines.
• Strong written and verbal English communication.

Responsibilities

• Develop, implement, and validate ML models, pipelines, and inference systems.
• Implement or modify model components and data pipelines using Python.
• Build reproducible workflows with Python, CLI, and ML frameworks.
• Debug numerical and system-level issues to find root causes.
• Optimize training and inference for memory, speed, and throughput.
• Design tests to verify correctness and performance requirements.
• Review complex ML tasks and validate proposed solutions.
• Use coding agents to accelerate development, debugging, and code reviews.
• Document approaches, decisions, tests, and performance findings clearly.
• Deliver high-quality, reproducible submissions within deadlines.

Skills

Python

ML engineering

Coding agents

Quantitative reasoning

Problem solving

Technical writing

English communication

Education

Master’s degree or PhD in a quantitative discipline

Tools

ML frameworks

Python development workflows

Job description

Gramian Consultancy seeks an experienced Machine Learning Research & Engineering Specialist for an advanced AI training project. You will develop, train, and optimize ML models, inference systems, and numerical methods in Python, with a focus on reproducible pipelines and robust engineering practices.

You will work on challenging ML tasks, validate results, and use coding agents within a Python workflow to accelerate development.