Computational Structural, Mechanical Engineering Expert

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop complex computational scientific and engineering challenges for evaluating AI benchmarks.

• Create innovative, graduate-level problems rooted in authentic scientific workflows.

• Construct challenges that involve simulations, analysis of results, experimental design, and extracting insights from data.

• Formulate tasks that necessitate specialized scientific software and intricate multi-step workflows.

• Devise strategic queries or experimental sequences to reveal concealed information from incomplete results.

• Evaluate each problem against cutting-edge AI models.

• Continuously refine problems until they achieve the desired level of complexity.

• Author problem setups, oracle functions, and validation solutions.

• Operate independently while integrating feedback into problem development.

• Partner with top researchers on initiatives aimed at training and improving AI systems.

⛳️ Requirements

• Graduate-level education in a relevant STEM discipline (MS, PhD, or equivalent research experience).

• Demonstrated expertise with at least one specified scientific software library, validated through research publications, open-source contributions, or professional experience.

• Strong proficiency in Python for creating problem setups, oracle functions, and solution validators.

• Capability to work autonomously and enhance problem designs based on input.

• Experience working comfortably in a Linux/terminal environment with remote compute sandboxes.

• Availability for a minimum of 15–20 hours per week.

• Practical experience utilizing domain-specific computational tools, rather than purely theoretical knowledge.

• Experience coding with scientific libraries to address actual research challenges.

• Awareness of tool limitations, edge cases, and authentic sources of problem difficulty.

• Nice to have: experience across multiple specified domains or tools.

• Nice to have: familiarity with benchmark or evaluation design.

• Nice to have: experience in scientific teaching or designing exams/problem sets.

• Nice to have: experience with computational reproducibility and containerized environments.

• Must not require H1-B or STEM OPT sponsorship; Mercor is unable to support H1-B or STEM OPT candidates.

🏝️ Benefits

• Fully remote position.

• Flexible scheduling.

• Weekly payments via Stripe or Wise based on services provided.

• Project durations may be extended, shortened, or concluded early based on requirements and performance.

• Competitive compensation.

• Collaboration with leading researchers.

• Opportunity to influence the development of future AI systems.

• Reasonable accommodations available upon request.

• Up to $400 for each successful referral.

• No limit on the number of referrals.