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.
Systems Engineer (Hardware)
Systems Engineers in this slug lead system-level integration of hardware, software, and mechanical subsystems for physical products and infrastructure—across two broad clusters. The first is AI-powered physical products: autonomous vehicles, robotics, satellites, and defense systems, where the role spans architecture, requirements, and verification across cross-functional engineering teams. The second is large-scale physical computing infrastructure: AI data centers and modular compute systems, where the role centers on integrating mechanical, electrical, and thermal subsystems and leading commissioning and validation activities through deployment. Both clusters share the underlying craft of system-level integration, requirements management, and cross-domain coordination. These engineers typically sit within hardware, systems, or infrastructure engineering organizations, working alongside domain specialists in mechanical, electrical, software, and operations functions.
Chip & Silicon Engineer
Chip & Silicon Engineers at AI companies work across the chip-design lifecycle for AI accelerators and supporting silicon—from RTL and microarchitecture through physical design, verification, and post-silicon validation. The role spans front-end design (architecting blocks, writing RTL, running simulation), physical design (synthesis, place-and-route, timing closure, power-performance-area optimization), and post-silicon work (bring-up, characterization, debug across hardware, firmware, and software layers). Specialization within this slug varies—some engineers focus narrowly on one phase of the pipeline, others coordinate across phases—but the population spans the full chain rather than concentrating on any single stage. These engineers typically sit within silicon, hardware, or platform engineering organizations at chip-focused AI companies, collaborating closely with verification, software, and systems teams to deliver production silicon.
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.
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.
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.
Robot Operator
Humanoid robot operators, robotics service technicians, and field operations roles at AI-robotics companies.
Industrial Technician
Manufacturing technicians, plant maintenance, and skilled trades roles supporting AI hardware production and AI infrastructure manufacturing.
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.
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.
Vehicle Operator
Vehicle operations roles at autonomous vehicle companies — CDL operators, fleet specialists, and vehicle service technicians.
Recent Jobs
The latest Physical Systems openings across the AI industry.