STEM Computational Scientific Software & Evaluation Design - Structural & Mechanical Engineering (Train AI Models Part Time!)
hackajob · United States
- Hybrid
- Full-time
- $70,000 / year
- United States
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Subject: Interested in the STEM Computational Scientific Software & Evaluation Design - Structural & Mechanical Engineering (Train AI Models Part Time!) role at hackajob
Hi Taylor — I came across the STEM Computational Scientific Software & Evaluation Design - Structural & Mechanical Engineering (Train AI Models Part Time!) opening and wanted to reach out directly. I've spent the last few years doing exactly this kind of work, and hackajob stood out because…
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Job highlights
- Design advanced AI reasoning problems.
- Utilize scientific software for complex tasks.
- Calibrate problems with state-of-the-art AI.
- Requires MS/PhD in STEM.
- Part-time, 15-20 hours/week.
About the role
STEM Computational Scientific Software & Evaluation Design - Structural & Mechanical Engineering
hackajob is collaborating with Mercor to connect them with exceptional professionals for this role.
About the Project
We're building a large-scale evaluation benchmark for advanced AI reasoning across scientific and engineering domains. Our task designers create challenging computational problems that test whether AI systems can use real scientific software tools to solve research-grade problems from querying simulations and interpreting outputs to designing experimental strategies and recovering hidden information from data. This is not a typical annotation or labeling role. You'll be designing original, graduate-level computational problems grounded in real scientific workflows, calibrating them against frontier AI models, and iterating on problem design until the difficulty is right.
What You'll Do
You'll design problems that require sophisticated use of domain-specific scientific software libraries. Some problems will require computing precise outputs from fully specified setups — testing whether a solver can correctly implement complex multi-step scientific workflows. Others will require something harder: designing a sequence of queries or experiments to uncover information that isn't directly visible, demanding strategic reasoning about what to measure, how to interpret partial observations, and how to narrow down possibilities efficiently. Each task goes through a calibration loop where it's tested against state-of-the-art AI models, and you'll refine the problem design until the difficulty hits the target range.
Domains & Tools We're Hiring For
We're especially interested in experts with deep, hands-on experience in the following area:
- Structural & Mechanical Engineering: Working with scikit-fem or similar finite element libraries for beam analysis, elasticity problems, and computational mechanics. Experience with Timoshenko beam theory, mesh convergence studies, or variational formulations is valuable.
*experience with other specialized software for the above domain will also be considered
What Makes a Strong Candidate
You have graduate-level expertise (MS or PhD preferred) in the domain listed above, with **real hands-on experience using the specific software tools**, not just theoretical knowledge of the field. You've **written code** that calls these libraries to solve actual research problems, and you understand where they break, what their edge cases are, and what makes a problem genuinely hard versus superficially complex. Beyond domain expertise, the strongest candidates will be able to think like a puzzle designer: constructing problems where the difficulty comes from reasoning strategy rather than brute computation, where there are multiple plausible approaches but only careful analysis reveals the right one, and where surface-level pattern matching won't get you to the answer.
Requirements
- Graduate-level training in a relevant STEM domain (MS, PhD, or equivalent research experience)
- Demonstrated proficiency with at least one of the listed scientific software libraries, evidenced by research publications, open-source contributions, or professional work
- Strong Python programming skills — you'll be writing problem setups, oracle functions, and solution validators
- Ability to work independently and iterate on problem designs based on calibration feedback
- Comfortable working in a Linux/terminal environment with remote compute sandboxes
- Available for at least 15–20 hours per week
Nice to Have
- Experience across multiple listed domains or tools
- Familiarity with benchmark or evaluation design
- Background in scientific pedagogy or exam/problem-set design
- Experience with computational reproducibility and containerized environments
Key skills/competency
- Computational Problem Design
- Structural Engineering
- Mechanical Engineering
- Finite Element Analysis
- Python Programming
- Scientific Software Libraries
- AI Model Evaluation
- Problem Calibration
- Research & Development
- Linux Environments
Skills & topics
- Computational Scientific Software
- Structural Engineering
- Mechanical Engineering
- AI Model Evaluation
- Python
- scikit-fem
- Finite Element Analysis
- Research
- Problem Design
- Part-time
How to get hired
- Tailor your resume: Highlight your MS/PhD, Python skills, and specific engineering domain experience (Structural/Mechanical).
- Showcase software proficiency: Detail your hands-on experience with scientific libraries like scikit-fem.
- Demonstrate problem-solving: Provide examples of how you've designed complex problems or used code to solve research challenges.
- Quantify impact: If possible, mention contributions to publications, open-source projects, or professional work.
- Emphasize AI evaluation: Mention any experience with benchmark design or evaluating AI models.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the main goal of this role at Mercor via hackajob?
- The main goal is to design challenging computational problems for advanced AI reasoning, specifically within Structural and Mechanical Engineering domains, using scientific software and calibrating against AI models.
- Is this a full-time position for a Computational Scientific Software Engineer?
- No, this is a part-time role, requiring approximately 15-20 hours per week.
- What are the primary technical skills required for this job?
- Strong Python programming skills are essential, along with hands-on experience using scientific software libraries like scikit-fem for Structural and Mechanical Engineering problems.
- What educational background is preferred for this role?
- Graduate-level training in a relevant STEM domain is preferred, with a Master's (MS) or PhD being ideal. Equivalent research experience will also be considered.
- Does Mercor at hackajob look for theoretical knowledge or practical application?
- Mercor is looking for real, hands-on experience using specific software tools and writing code to solve actual research problems, not just theoretical knowledge.
- What is the role of AI model calibration in this position?
- You will be involved in a calibration loop where designed problems are tested against state-of-the-art AI models, and you will refine the problem design based on this feedback.
- What specific engineering domain is Mercor most interested in?
- Mercor is particularly interested in experts with deep, hands-on experience in Structural & Mechanical Engineering.
- What kind of problems will I be designing?
- You will design graduate-level computational problems that require sophisticated use of scientific software libraries to solve research-grade problems, some involving direct computation and others requiring strategic reasoning to uncover hidden information.