Vehicle Design Specialist - AI Trainer

Obsidian; Detroit (MI); On-site; USD 1,584,240 - 1,997,520; Part time

Benefits offered by this job

Performance bonus for top performers

Hourly compensation opportunities for good quality

Job summary

Obsidian is looking for experienced automotive mechanical engineering professionals in Detroit for Project Atlas, focusing on building realistic enterprise environments for AI agents. Candidates must have experience with Fortune 500 automotive OEMs or Tier-1 suppliers.

The ideal candidate will have expertise in vehicle engineering and proficiency in tools like ANSYS Fluent. Competitive pay is offered per completed task, with bonus incentives for top performers.

Qualifications

• 3+ years of full-time experience at a Fortune 500 automotive OEM or Tier-1 supplier.
• Experience in vehicle or subsystem design.
• Proficiency in CAE / CAD / simulation engineering.

Responsibilities

• Build realistic digital workspaces based on day-to-day tools.
• Design multi-step tasks for navigating complex workflows.
• Collaborate with other experts to review scenarios for realism.

Skills

Vehicle design expertise

Powertrain engineering

Manufacturing engineering

Analytical thinking

Education

BS/MS in Mechanical Engineering or related discipline

Tools

ANSYS Fluent

SAP S/4HANA

Siemens Opcenter

Job description

Role Overview

Mercor is partnering with leading AI labs on Project Atlas — an initiative to build realistic enterprise environments that frontier AI agents are trained and evaluated in. We're seeking experienced automotive mechanical-engineering professionals from Fortune 500 OEMs and major Tier-1 suppliers (e.g., GM, Ford, Stellantis, Tesla, Toyota North America, Magna, Bosch, Denso, Aptiv) to recreate the digital workspaces they run every day and design the tasks that genuinely challenge state‑of‑the‑art AI.

You’ll bring your expertise in vehicle design, powertrain / chassis engineering, manufacturing engineering, or automotive quality to build a high‑fidelity environment that mirrors the tools, files, and cross‑functional workflows of a modern automotive enterprise — and then author tasks grounded in the programs you actually run today.

Key Responsibilities

• Build a realistic digital workspace centered on the Drive folders you use day‑to‑day — the design reviews, DFMEA / PFMEA documents, PPAP packages, tolerance analyses, benchmarking decks, test reports, and email threads that reflect how you actually organize your work — with some representation of the platforms that support it (e.g., ANSYS Fluent / STAR‑CCM+, Siemens Opcenter, SAP S/4HANA)
• Design multi-step tasks grounded in your real workflows that require navigating multiple apps, files, and stakeholders in a way that meaningfully challenges frontier AI agents
• Collaborate with other automotive engineering experts in your field to design the environment, shape task scope, and review each other's scenarios for realism and rigor
• Work asynchronously with research teams to refine task designs and evaluation criteria for automotive engineering agent benchmarks
• Contribute to frontier AI research and benchmarking — the work you produce directly informs how leading labs train and evaluate the next generation of AI systems

Ideal Qualifications

• BS/MS in Mechanical Engineering or related discipline
• 3+ years of full-time experience at a Fortune 500 automotive OEM or Tier-1 supplier
• Background in one or more areas such as:
• Vehicle or subsystem design (body, chassis, interior, powertrain, thermal)
• CAE / CAD / simulation engineering (structural, NVH, CFD, durability)
• Manufacturing / process engineering (stamping, body‑in‑white, assembly, paint)
• Quality engineering under IATF 16949 / APQP / PPAP
• EV / battery / ADAS engineering
• Day‑to‑day use of ANSYS Fluent / STAR‑CCM+, Siemens Opcenter or Rockwell FactoryTalk, and SAP S/4HANA
• Strong analytical thinking and writing — able to translate automotive engineering workflows into structured task specs

Compensation Note

• Task Completion Pay: Competitive and based on task quality (~$1,150 – $1,450 per completed task, subject to change as the project evolves)
• Performance Bonus: Top performers receive a weekly bonus incentive on top of their per task rate!
• Hourly Opportunity: Top performers may be invited to transition to an hourly compensation model based on sustained quality and throughput.