Physical Systems
Engineers, technicians, and operators working on hardware design, robotics, embedded systems, manufacturing, and safety-critical physical systems. Covers chip/silicon design, mechanical and electrical engineering, firmware/embedded software, robotics operations, systems safety, physical manufacturing, and datacenter hardware installation and cabling.
Roles
The canonical roles within Physical Systems.
Hardware & Electrical Engineer
Hardware & Electrical Engineers in AI companies design and optimize the physical systems that power AI infrastructure—from circuit boards and power delivery networks for AI accelerators to cooling systems and signal integrity in data center environments. They collaborate closely with firmware, software, and systems teams to translate performance requirements into manufacturable hardware, often working on high-speed interfaces, thermal management, and reliability validation for next-generation AI compute platforms. What distinguishes this work is the focus on solving real-time performance bottlenecks at scale: ensuring power delivery meets demanding AI workloads, managing thermal challenges in liquid-cooled systems, and validating signal integrity across complex interconnects that directly impact model training and inference speeds. These engineers typically sit within hardware engineering or infrastructure teams at AI hardware companies, robotics firms, or cloud providers building AI-optimized data centers, working alongside cross-functional teams of systems architects, firmware engineers, and manufacturing partners.
Chip & Silicon Engineer
Engineers in this role lead the validation and characterization of advanced AI accelerator chips after they return from manufacturing, working across silicon, firmware, and platform layers to prove functional correctness and performance under production conditions. They distinguish themselves by combining hands-on silicon debugging expertise with the ability to coordinate complex cross-domain issues spanning hardware, software, and systems integration—moving beyond traditional post-silicon testing to architect validation strategies for next-generation high-performance SoCs. These roles typically sit within Manufacturing Operations or Architecture and Validation teams at semiconductor-focused AI companies, collaborating closely with logical design, physical design, verification, and software teams to translate silicon specification into reliably deployed products at scale.
Technician & Skilled Trades
Technicians in this role perform hands-on inspection, maintenance, troubleshooting, and repair of robots, hardware systems, and manufacturing equipment in AI companies. They verify material quality and equipment performance, diagnose mechanical and electrical faults using specialized tools, and document issues for engineering teams to improve product reliability. These roles distinguish themselves by requiring both deep technical expertise in complex electromechanical systems and the ability to work collaboratively with design and engineering teams to drive rapid iteration. Technicians typically sit within hardware, operations, or fleet management teams where they serve as the critical bridge between field reality and engineering innovation, directly enabling the deployment of AI-powered robotic systems.
Datacenter Field Technician
Datacenter Field Technicians execute the physical deployment and maintenance of AI infrastructure, performing hands-on installation, cabling, and troubleshooting of GPU servers, networking systems, and supporting hardware across data center environments. They distinguish themselves through deep expertise in critical infrastructure systems—power distribution, thermal management, fiber optics, and structured cabling—combined with the ability to diagnose and resolve complex hardware issues in GPU-dense deployments that power large-scale AI workloads. These technicians typically work within dedicated infrastructure or operations teams at AI cloud providers and hardware-focused companies, collaborating closely with hardware engineers, project managers, and remote support staff to ensure new deployments move from installation through production readiness with precision.
Embedded & Firmware Engineer
Engineers in this role develop and optimize firmware that powers AI infrastructure hardware—from baseboard management controllers in data centers to motor controllers in robotics systems to camera sensor drivers in vision platforms. They work at the boundary between silicon and software, writing low-level C/C++ code to manage power, thermal systems, sensors, and real-time control, often using RTOS environments and debugging with JTAG and oscilloscopes. This work distinguishes itself from higher-level embedded software engineering by its focus on board bring-up, hardware validation, and tight hardware-firmware integration during product bringup. These engineers typically sit in hardware-adjacent teams within AI companies—working closely with silicon teams, hardware engineers, and systems architects to ensure new AI chips and platforms function reliably at scale in production environments.
Systems Engineer (Hardware)
Engineers in this role lead the integration of hardware, software, and mechanical systems for AI-powered physical products like satellites, autonomous vehicles, and defense platforms. They own system-level architecture, requirements definition, and verification across multiple domains—translating complex operational scenarios into verifiable specifications and ensuring all subsystems work together reliably. Positioned as technical authorities within their organizations, they bridge cross-functional teams including payload specialists, security engineers, and software architects to manage trade-offs and drive systems from concept through deployment and operation.
Manufacturing & Production Engineer
Engineers in this role guide the journey of AI hardware—from prototype to mass production—designing and optimizing manufacturing processes for PCBs, assemblies, and mechatronic systems. They partner with design teams, contract manufacturers, and cross-functional stakeholders to solve complex manufacturability challenges, conducting detailed design-for-manufacturing reviews and managing new product introductions while scaling production efficiency and quality. Typically embedded within hardware or operations teams at AI companies building inference systems, robots, or autonomous vehicles, they balance technical rigor with hands-on problem-solving, translating engineering intent into reliable, repeatable factory processes.
Systems Safety Engineer
Systems Safety Engineers at autonomous vehicle and robotics companies conduct comprehensive hazard analyses, risk assessments, and functional safety evaluations to ensure AI-driven systems operate safely in real-world environments. They lead cross-functional efforts to define safety requirements, develop mitigation strategies, and verify that implemented controls effectively reduce risk across hardware, software, and operational domains. What distinguishes this role is its focus on safety-critical AI systems where failures can directly impact human safety, requiring deep engagement with international standards like ISO 26262 and continuous validation against field data. These engineers typically embed within dedicated safety teams, working alongside product, engineering, and regulatory stakeholders to navigate novel safety challenges in emerging autonomous technologies.
Robotics Engineer
Robotics engineers in this role design and implement the complete software and control systems that make physical robots function in real-world environments—from manipulation and locomotion to perception and autonomous navigation. They write production-level C++ and Python code for controllers, planners, and perception stacks, translating machine learning models developed by researchers into deployed robotic behavior. Working closely with ML engineers and hardware teams, they tackle the full robotics stack: tuning control algorithms, debugging electromechanical systems, optimizing performance on real hardware, and ensuring robots operate reliably across deployment sites. This role differs from simulation-focused positions by requiring hands-on hardware integration, real-time system debugging, and direct responsibility for robot behavior in production environments rather than purely algorithmic research.
Recent Jobs
The latest Physical Systems openings across the AI industry.