Home › Jobs › Deutschland › Structural Engineering Specialist - Fully Remote | Upto $85/hr
🇪🇺 Deutschland • Permanent

Structural Engineering Specialist - Fully Remote | Upto $85/hr

🏢 mercorhttps://static.whatjobs.com/static/ajCore/img/jobPosting/companyLogo/whatJobs_ob_default.png 📍 📅 23 October 2026

Job Description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .

Position: Computational Structural & Mechanical Engineering Expert

Type: Contract

Compensation: $70–$85/hour

Location: Remote

Commitment: 15–20 hours/week

Role Responsibilities

  • Design challenging computational problems to test AI capabilities in solving scientific and engineering tasks.
  • Develop problems requiring skilled use of open-source, domain-specific computational tools like FEniCSx/DOLFINx , OpenFOAM , deal.II , and others.
  • Evaluate AI models by testing them against state-of-the-art benchmarks and refine problems to achieve the desired difficulty.
  • Collaborate with AI research teams to improve problem designs and ensure they test strategic reasoning and problem-solving.
  • Work independently and asynchronously to meet deadlines and refine problem designs based on feedback.

Qualifications

Must-Have

  • Graduate-level training in a relevant STEM field ( MS, PhD, or equivalent research experience ).
  • Proven proficiency with at least one of the listed scientific software libraries through research publications, open-source contributions, or professional work.
  • Strong Python skills for writing problem setups, oracle functions, and solution validators.
  • Ability to work independently and refine problem designs based on feedback.
  • Comfortable working in a Linux/terminal environment with remote compute sandboxes.

Preferred

  • Experience across multiple listed domains or tools.
  • Familiarity with benchmark or evaluation design.
  • Background in scientific teaching or exam/problem-set design.
  • Experience with computational reproducibility and containerized environments.
#J-18808-Ljbffr

Ready to apply for this position?

Apply directly through the official application portal.

Apply Now →