Head of Hardware

• Bachelor’s degree in mechanical engineering, mechatronics, robotics, electrical engineering, or a related discipline or equivalent practical experience.
• Typically 8+ years of experience developing complex mechanical, electromechanical, robotic, automation, or sensing systems.
• A track record of leading technically complex hardware programs from ambiguous requirements through architecture, detailed design, validation, production, and field deployment.
• Experience leading design reviews, resolving cross-functional technical disagreements, and leading and growing engineering teams.
• Demonstrated ownership of systems containing interacting mechanical, electrical, optical, software, and operational elements.
• Deep proficiency with a modern 3D CAD platform such as SolidWorks, Onshape, Creo, or NX.
• Strong command of mechanical engineering fundamentals, including tolerance analysis, GD&T, structural design, materials, fasteners, bearings, actuators, cable management, and manufacturing processes.
• Experience designing production-quality parts and assemblies and creating drawings, bills of materials, assembly procedures, and configuration-controlled documentation.
• Hands-on experience integrating cameras, sensors, actuators, embedded compute, networking, and power systems.
• Experience designing verification, qualification, lifecycle, and reliability tests for complex hardware.
• Strong systems-engineering judgment and the ability to make clear tradeoffs among performance, schedule, reliability, cost, manufacturability, and serviceability.
• Ability to communicate effectively with engineers, operators, suppliers, executives, and customers.
• Willingness to work hands-on with hardware and travel to customer sites as needed.

• Experience developing robotic grippers, custom fingers, tool changers, compliant mechanisms, tactile or force-sensing systems, or other manipulation hardware.
• Experience architecting industrial robot, cobot, laboratory automation, warehouse automation, or machine-vision workcells.
• Experience developing hardware used specifically for robot learning, teleoperation, demonstration collection, or large-scale robotics datasets.
• Experience with machine safety and robotics standards such as ISO 10218, ISO/TS 15066, ANSI/RIA R15.06, or related customer-site requirements.
• Experience with DFMEA, fault-tree analysis, tolerance analysis, accelerated lifecycle testing, environmental qualification, and formal engineering change control.
• Experience managing technical relationships with strategic suppliers, contract manufacturers, and external system integrators.

• Define the technical architecture and long-term roadmap for robotic data-collection systems and customer-deployed workcells.
• Build and lead the hardware team as we scale. Define the roles we need, hire exceptional engineers, and set the bar for how the team designs, builds and ships.
• Translate company, product, model-training, and customer requirements into scalable hardware platforms and subsystem specifications.
• Own system-level tradeoffs across mechanical design, sensing, controls, compute, safety, reliability, manufacturability, serviceability, cost, and deployment speed.
• Identify the highest-risk technical problems, establish validation strategies, and drive programs from ambiguous requirements to reliable deployed systems.
• Establish design principles, interfaces, qualification standards, documentation practices, and configuration-management processes across the hardware organization.
• Lead architecture reviews, design reviews, failure investigations, and technical readiness assessments for critical hardware programs.
• Serve as a technical authority for complex decisions spanning mechanical, electrical, optical, software, and operational domains.

• Architect robotic data-collection platforms that produce consistent, high-quality training data across operators, tasks, sites, and robot configurations.
• Partner with ML and data teams to determine how embodiment design, sensor placement, calibration, latency, repeatability, and hardware variation affect data quality and policy performance.
• Define system requirements for payload, workspace, stiffness, compliance, precision, visibility, ergonomics, cycle life, safety, and operator throughput.
• Develop modular architectures that allow new sensors, end effectors, robots, and task fixtures to be integrated without redesigning the entire platform.
• Establish instrumentation and telemetry strategies that make hardware health, configuration, calibration, and data-quality issues observable across the fleet.

• Lead the design and development of end effectors, including grippers, custom fingers, tool interfaces, compliant mechanisms, force-sensing elements, and quick-change systems.
• Translate manipulation-task requirements and policy failure modes into actionable hardware improvements.
• Develop reusable end-effector architectures that balance dexterity, robustness, sensing, manufacturability, weight, cost, and serviceability.
• Drive analytical and empirical validation of grasping performance, structural integrity, compliance, repeatability, wear, and lifecycle durability.
• Guide make-versus-buy decisions and evaluate commercial components, custom mechanisms, actuators, sensors, and manufacturing approaches.

• Define reference architectures for complete robotic workcells incorporating robot arms, end effectors, cameras, compute, networking, power distribution, safety systems, fixtures, and operator interfaces.
• Lead technical discovery for customer deployments, including site surveys, task analysis, risk identification, and requirements definition.
• Resolve constraints involving layout, reachability, utilities, networking, lighting, environmental conditions, safety, workflow integration, and service access.
• Partner directly with customers and internal deployment teams during installation, commissioning, acceptance testing, troubleshooting, and system upgrades.
• Create deployment standards, acceptance criteria, maintenance strategies, spare-parts plans, and escalation procedures that enable systems to be supported at scale.
• Use lessons from field deployments to improve the core hardware platform and reduce installation time, service burden, and site-specific engineering.

The listed range reflects base salary only. Total compensation also includes meaningful equity and benefits:

• Equity: Meaningful ownership in what we’re building.
• Health coverage: Medical, dental and vision through Thatch.
• Team lunches: Lunch in the office with the team.

Our benefits will keep growing as we do. If the work excites you, please apply. We’d love to talk!

We encourage candidates from all backgrounds to apply, even if you don't feel like you're a perfect fit. If you're passionate about contributing to our mission, we'd love to hear from you!

Nidus is building autonomous manufacturing systems powered by AI and robotics. U.S. manufacturers are under growing pressure to increase output while navigating workforce constraints, underutilized equipment, and increasingly complex supply chains. We believe the next generation of manufacturing will be enabled by more intelligent, flexible automation—systems that help people and machines work together to expand capacity and improve productivity.

We're building the intelligence layer that makes that possible.

Our team comes from the intersection of defense technology and AI. We've built and shipped products to DoD customers, and we bring deep experience across ML, robotics, product development, and defense.

We're a small, in-person team in New York City working on hard problems that matter. If you want to build the future of American manufacturing, we'd love to hear from you.