Synthires
Materials Science & Engineering Specialist (Remote | $60–$90/hr)

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Materials & Engineering Specialist
Position: Materials & Engineering Specialist
Type: Hourly Contract
Compensation: $60–$90/hour
Location: Remote
About the Opportunity
This opportunity is for experienced materials science, electrical engineering, and mechanical engineering professionals to contribute to advanced AI research and evaluation projects.
You'll apply your real-world engineering expertise to design realistic technical tasks, build supporting data rooms and evaluation criteria, assess AI-generated solutions, and refine tasks to accurately measure expert-level engineering reasoning.
The role is ideal for professionals who can navigate complex technical problems, ambiguity, engineering constraints, and nuanced trade-offs while clearly explaining both correct and incorrect approaches.
Responsibilities
- Author domain-authentic engineering tasks based on real-world professional experience.
- Develop realistic technical prompts, supporting documentation, datasets, and data rooms.
- Create objective grading criteria and evaluation rubrics for engineering tasks.
- Run engineering tasks against AI models and analyze the quality of generated solutions.
- Identify technical errors, weak assumptions, gaps in reasoning, and incorrect engineering approaches.
- Iterate on tasks and evaluation criteria to ensure they effectively distinguish expert-level engineering judgment.
- Explain not only the correct engineering solution but also why alternative or incorrect solutions fail.
- Collaborate with project leads and other engineering experts to establish appropriate technical standards.
- Apply professional engineering judgment when dealing with ambiguous or incompletely defined problems.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
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Required Qualifications
- Strong professional expertise in at least one relevant engineering discipline:
- Materials Science: metals, ceramics, composites, characterization, additive manufacturing.
- Electrical Engineering: analog, RF, power systems.
- Mechanical Engineering: mechanical design, CFD and fluids, heat transfer, pressure vessels, NDE, CAE.
- Demonstrated ability to solve complex technical engineering problems.
- Strong understanding of engineering principles, methodologies, and real-world constraints.
- Ability to evaluate technical solutions and identify subtle errors or unrealistic assumptions.
- Strong analytical and critical-thinking skills.
- Ability to clearly explain why a technical solution is correct or incorrect.
- Comfortable working independently in a remote environment.
- Strong written communication skills and attention to technical detail.
Preferred Qualifications


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- Senior-level professional experience in materials science, electrical engineering, or mechanical engineering.
- Experience working on complex engineering projects involving design, analysis, testing, simulation, or characterization.
- Experience creating or reviewing technical documentation, engineering reports, datasets, or evaluation criteria.
- Familiarity with engineering software, simulation tools, laboratory workflows, or technical data analysis.
- Experience with AI evaluation, technical benchmarking, or AI training projects is a plus, but not required.
- Comfortable working through ambiguous technical requirements and defining what constitutes a high-quality solution.
Compensation
- Competitive compensation of $60–$90/hour.
- Hourly contract engagement.
- Fully remote with flexible work arrangements.
- Daily onboarding sessions and multiple office hours available.
- Opportunity to contribute to advanced AI training and evaluation projects.
Application Process
- Apply to the role
- Complete the required screening questions
- Provide details about your engineering background and specialization
- Complete the relevant technical assessment or evaluation
- Participate in onboarding sessions
- Hiring/project team review
- Begin contributing to engineering AI evaluation tasks
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