Engineering Design Specialist (Remote)
💡 טיפ להגשת מועמדות: לחיצה על "הגש מועמדות ב-Braintrust בחינם" תעביר אתכם לאתר הרשמי של Braintrust. זה 100% חינם עבורכם ועוזר לתמוך בפלטפורמה שלנו באמצעות בונוסי הפניה.
⚠️ הערת תרגום: מידע המשרה תורגם באמצעות בינה מלאכותית. במקרה של חוסר דיוק או אי־בהירות, יש להסתמך על הגרסה המקורית באנגלית.
Role Overview
About Turing
Based in San Francisco, California, Turing is the world's leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L
Role Overview
We are looking for experienced engineers with deep design expertise to create challenging, simulation-based design problems for training and evaluating advanced AI models. The role focuses on crafting realistic engineering design tasks where a model must make genuine trade-offs, size components, and iterate against physics-based simulators to meet competing specifications.
Key Responsibilities
- Design and validate simulation-based engineering problems that require true design reasoning, with clear constraints and optimization goals.
- Deliver complete problem sets including reference solutions, near-miss variants, edge cases, and documentation, ensure appropriate difficulty with multiple failure modes, and collaborate with researchers to refine problems based on model performance.
Domain Tracks
- You should have deep design expertise in at least one of the following; expertise spanning multiple tracks is a strong plus.
- Electrical & Computer Engineering - analog/mixed-signal IC design, power electronics, RF/microwave, digital system design, FPGA/ASIC, embedded systems.
- Mechanical Engineering - structural/thermal/fluid system design, mechanism design, HVAC, vibration/dynamics, manufacturing process design.
- Chemical Engineering - reactor design, process design and optimization, separation systems, transport phenomena, combustion and thermochemistry.
- Control Systems - classical and modern control design, state estimation, nonlinear and robust control, system identification.
- Materials / Nano - materials selection under constraints, microstructure-property design, thin-film and nanoscale device design.
- Engineering Physics / Optics - optical system design, photonic device design, laser systems, wave propagation and interference.
- Aerospace Engineering - aerodynamic design, propulsion sizing, orbital mechanics, flight dynamics and stability, structural design for aerospace loads.
- Civil / Structural Engineering - structural member and connection design, foundation design, seismic/wind loading, geotechnical design.
- Nuclear / Energy - reactor core design, shielding, thermal-hydraulics, renewable energy system sizing, grid-scale storage design.
- Systems Engineering - system architecture trade studies, requirements decomposition, interface design, multi-subsystem integration.
- Robotics - kinematic/dynamic design, motion planning, actuator and sensor selection, mechatronic system integration.
Required Qualification:
- Master's or PhD in a relevant engineering/applied science field.
- 3+ years of hands-on engineering design experience, producing validated designs from competing specs (not just analysis).
- Proficient in at least one open-source simulation tool relevant to the domain.
- Strong Python (or equivalent) scripting skills.
- High attention to detail across units, boundary conditions, convergence, and physical realism.
Nice to Have
- Experience designing engineering coursework, exam problems, or design challenges at graduate level.
- Familiarity with CI/CD pipelines or automated testing frameworks.
- Exposure to LLM evaluation, AI benchmarking, or training data curation.
- Cross-domain familiarity with Control Systems, Embedded/Robotics, or Power Systems.
Evaluation Process
- Shortlisted candidates will be sent a Job Interest Form.
- Shortlisted candidates will receive a Job Interest Form. After the initial profile review, we will share an assessment, which must be completed within 24 hours. Based on the assessment submission and your responses, we may schedule an interview round.
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