Remote Hardware Engineer for AI Training (Contractor)

Synthires; United States; Remote; USD 83,000 - 165,000; Part time

Job summary

Synthires is seeking a Hardware Expert (MSc or PhD) for a fully remote, contract-based role to support AI training projects. You will create technically rigorous hardware engineering problems based on realistic scenarios, and develop reproducible reference solutions.

You will validate results with appropriate tools, apply first-principles reasoning, and design challenges that test technical judgment and quantitative problem-solving.

Qualifications

• Significant professional or research experience in hardware engineering.
• Ownership of substantial engineering projects, testing, validation, or failure analysis.
• Experience working with coding agents.
• Strong quantitative reasoning and technical problem-solving skills.
• Ability to develop accurate, well-documented, and reproducible engineering solutions.

Responsibilities

• Create technically rigorous hardware engineering problems based on realistic industry or research scenarios.
• Develop clear, reproducible reference solutions using calculations, simulations, scripts, or experimental reasoning.
• Validate results using appropriate engineering tools and software.
• Apply first-principles reasoning to practical engineering constraints.
• Design challenges that assess technical judgment, quantitative reasoning, and problem-solving.
• Ensure solutions can be independently verified.

Skills

Quantitative reasoning

Technical problem solving

Coding agents experience

Documentation of solutions

Education

Electrical Engineering degree

Tools

Python

MATLAB

Simulink

SPICE

Julia

C/C++

Test automation

Job description

Synthires is seeking a Hardware Expert (MSc or PhD) for a fully remote, contract-based role to support AI training projects. You will create technically rigorous hardware engineering problems based on realistic scenarios, and develop reproducible reference solutions.

You will validate results with appropriate tools, apply first-principles reasoning, and design challenges that test technical judgment and quantitative problem-solving.