Electronics engineer • carlsbad ca
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 ...Show more
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Job Summary (List Format): - Industry: Communications - Location: Carlsbad, CA (5 days onsite, not remote) - Interview Type: Video - Key Responsibilities: - Develop and build automation scripts and...Show more
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The average salary range is between $ 114,400 and $ 170,000 year , with the average salary hovering around $ 170,000 year .
The average salary range is between $ 90,230 and $ 152,500 year , with the average salary hovering around $ 108,949 year .
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 electronics-manufacturing and hardware-engineering professionals from Fortune 500 semiconductor, consumer-electronics, and networking-hardware companies (e.g., Intel, Texas Instruments, Analog Devices, Micron, Apple, Qualcomm, Broadcom, Nvidia, AMD, Cisco, TE Connectivity, Amphenol) 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 semiconductor design or fabrication, PCB / electronic-assembly, hardware test engineering, or electronics supply-chain to build a high-fidelity environment that mirrors the tools, files, and cross-functional workflows of a modern electronics 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 review decks, schematic / layout files, test reports, yield analyses, BOMs, ECOs, reliability / validation 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 simulations, Siemens Opcenter MES, GitHub / GitLab) - 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 electronics-manufacturing 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 electronics-manufacturing 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 Electrical Engineering, Computer Engineering, or related discipline - 3+ years of full-time experience at a Fortune 500 semiconductor, consumer-electronics, or networking-hardware company, or a major contract manufacturer (Foxconn, Flex, Jabil, Celestica) - Background in one or more areas such as : - Semiconductor design (digital / analog / mixed-signal, IC / SoC) - Semiconductor fabrication, process integration, or yield engineering - PCB design, electronic-assembly, or SMT manufacturing - Hardware test engineering, validation, or reliability (HALT / HASS) - Electronics supply-chain, sourcing, or NPI / sustaining engineering - Day-to-day use of ANSYS Fluent / STAR-CCM+, Siemens Opcenter or Rockwell FactoryTalk, and GitHub / GitLab - Strong analytical thinking and writing — able to translate electronics workflows into structured task specs Compensation Note This project is expected to begin on an effective hourly rate, but will transition to a model where experts are compensated based on throughput of quality work rather than a flat accruing hourly rate. About Mercor Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations. Backed by investors including Benchmark, General Catalyst, Adam D'Angelo, and Jack Dorsey. Thousands of professionals across domains contribute to projects shaping the next generation of AI systems.
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