About Mind

Mind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems. Join us if you want to move beyond digital intelligence and put intelligence into motion.

About the Role

We are looking for our Electrical Engineering Lead to own the end-to-end electrical architecture for our advanced robotic systems. This is a hands-on, deeply technical leadership role for an engineer who leads from the bench, personally driving schematic design, PCB layout, and low-level fault isolation, rather than managing from a distance.

As a technical authority and mentor, you will elevate the team’s standard for engineering excellence while making critical trade-offs across power electronics, motor drives, high-speed sensing stacks, and EtherCAT-based distributed actuation.

Responsibilities

• Lead, mentor, and scale the EE team (power electronics, sensing, and electrical design) while raising the technical bar through hiring and onboarding.

• Own the robot’s end-to-end electrical architecture (power, actuation, sensing, compute integration, and harnessing) and overall electrical budget.

• Set EE design standards, review schematics/layouts, and arbitrate trade-offs across signal integrity, EMI/EMC, thermals, and cost.

• Partner with mechanical, firmware, and perception teams to translate product requirements into hardware specs and integrate high-speed sensor stacks.

• Lead system-level electrical bring-up, fault isolation, and root-cause debugging across board boundaries from the lab bench.

• Establish lightweight, scalable workflows for design reviews, schematic/layout sign-offs, ECO discipline, and roadmapping.

• Drive DFM/DFA, collaborate with PCB fabricators and contract manufacturers, and secure second-source components for production ramp.

Qualifications

• Technical degree in EE (or equivalent) with 8+ years of full-cycle board development (schematic to production) for complex robotic, automotive, or electromechanical systems.

• A first-principles engineer who actively designs, lays out, and debugs hardware rather than managing purely from a distance.

• Deep, hands-on experience with EtherCAT (topology, distributed-clock sync, PDO mapping) for distributed actuation and sensing.

• Mastery of at least one core domain—power electronics/motor drives or sensor/mixed-signal front-ends—with broad fluency across both.

• Strong grasp of high-current power architectures, rail partitioning, budgeting, and circuit protection (OVP/UVP/OCP/OTP).

• Solid command of EMI/EMC, grounding, and ESD mitigation in noisy, motor-dense environments.

• Fluency with high-speed serial interfaces and protocols (SPI, I2C, UART, PMBus), plus enough firmware literacy to debug hardware boundaries.

• Proven experience mentoring engineers, managing risk, and driving multi-board hardware projects through volume manufacturing.

About Mind

Mind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems. Join us if you want to move beyond digital intelligence and put intelligence into motion.

About the Role

Human-like dexterity is one of the final frontiers in robotics. As a Mechanical Engineer on our Hands team, you will be responsible for designing, prototyping, and scaling the mechanical architecture of our dexterous hands and fingers. You will work at the intersection of high-precision mechanics, tactile sensing, and advanced manufacturing to build reliable, high-durability hardware that interacts directly with the physical world.

Responsibilities

• Design and development of mechanical components and assemblies for dexterous hands — fingers, linkages, transmissions, and palm structures

• Own designs from concept through production: parts that satisfy load conditions, durability, form factor, and packaging constraints in an extremely space-constrained envelope

• Rapidly build, test, and break prototypes to validate assembly, range of motion, grasp performance, and wire routing. You'll use 3D printing, CNC machining, and manual fabrication

• Integrate tactile sensors, actuators, motors, and wire harnesses into compact fingertip and palm geometries, working closely with the tactile sensing and actuation teams

• Generate accurate 2D drawings using GD&T (ASME Y14.5) and drive parts through supplier selection, first article inspection, and production ramp

• Develop specifications and accelerated life test plans (grasp cycles, impact, wear) to validate the hand for its lifetime

• Perform basic analyses (tolerance, structural, thermal) to validate design decisions

• Collaborate with cross-functional teams (electrical, firmware, controls, industrial design) to consolidate requirements and integrate the hand into the full robot system

Qualifications

• Exceptional mechanical intuition. You understand how forces, materials, and mechanisms behave instinctively — especially small, high-cycle mechanisms

• 3+ years of experience (or equivalent "hard tech" projects) building complex, miniaturized electromechanical systems — robotic hands, grippers, surgical robotics, prosthetics, precision mechanisms, or consumer wearables

• High proficiency in SolidWorks, Catia, or similar tools; comfortable designing complex geometry in tight packaging

• Experience with electromechanical integration — sensors, small motors, flex circuits, and wire harnesses in constrained volumes

• Hands-on problem-solving approach with the ability to iterate quickly

• Experience designing for volume processes (MIM, injection molding, micro-machining, CNC) and working with contract manufacturers

• You are comfortable with ambiguity, move fast, and have an "engineering curiosity" that drives you to understand how the entire hand-arm system works, not just your part

About Mind:

Mind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems. Join us if you want to move beyond digital intelligence and put intelligence into motion.

About the team and the role:

As an Application Engineer, you’ll be one of the founding engineers on the team that owns this application layer, reporting to our Head of Application Engineering. The systems work today; your job is to help harden and productionize them for scale — from 10 capture stations at one site to hundreds across multiple OEM plants, and from a handful of tele-operation stations to a multi-shift fleet. This is early, hands-on, 0-to-1 engineering: you’ll ship code that runs on real hardware in real factories, and see its effect on robot behavior.

Responsibilities:

• Build the field capture stack — edge software for our data collection rigs: device management, sensor orchestration, and real-time data quality monitoring that holds up on a factory floor.

• Ship the tele-operations stack — collection, evaluation, and operator tooling for our teleoperation stations, including metrics, task management, and the workflows our robot operators use every day.

• Streamline annotation methods/models to increase labelling efficiency.

• Make deployment repeatable — contribute to tooling and configuration systems that make onboarding a new manufacturing site a config change, not a custom engineering project.

• Support the field — debug issues on live systems, instrument for observability, and work directly with site operations staff and robot operators who depend on your software.

Requirements:

• 3+ years of software engineering experience building production systems.

• Strong programming fundamentals and comfort working across the stack — edge devices, services, and data pipelines.

• Experience with at least one of: real-time data pipelines, edge computing, device or fleet management, robotics or sensor systems.

• Bias for ownership: you’ve taken features or systems from prototype to production and supported them in the field.

• Clear communication and close collaboration with product, research, and operations partners.

• Hands-on experience with sensor data (video, depth, IMU, force/torque) and the infrastructure to process it at scale is a plus.

• Background in robotics, autonomous vehicles, industrial IoT, or teleoperation systems is a plus.

• Exposure to manufacturing or other industrial environments is a plus.

• Familiarity with ML data workflows (datasets, labelling, evaluation) is a plus.

About Mind:

Mind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems. Join us if you want to move beyond digital intelligence and put intelligence into motion.

About the Role

At Mind Robotics, we're building generalized physical AI — robotic systems capable of dexterous, adaptive, and reasoning-intensive work in real-world industrial environments. We’re hiring a Forward Deployed Engineer to be our hands and eyes onsite at a key customer in Normal, IL. You’ll be responsible for our fleet of data collection devices — diagnosing and repairing devices, provisioning new hardware, troubleshooting networking, and running the diagnostic workflows that keep the system healthy. This role will start with critical robot data collection devices and then transition into robot deployment support.

This is a forward-deployed role with strong support from HQ. You won’t be alone: our engineering team is one Slack message away, and you’ll work closely with them to escalate complex issues, ship fixes back into the product, and bring the voice of the customer into our roadmap. The ideal candidate is technically curious, calm under pressure, and energized by being the person on the ground who makes things work.

Responsibilities

• Provision new hardware by installing and configuring Linux, deploying our software stack, and validating device health before bringing units into production.

• Run diagnostic scripts, collect and interpret system logs, and execute command-line workflows to identify root causes of device or network issues.

• Configure and troubleshoot local networking (IP, DHCP, DNS, VLANs, Wi-Fi/Ethernet) to ensure reliable device connectivity to our backend.

• Serve as the customer’s primary technical point of contact onsite, coordinating closely with HQ engineering and support to resolve issues and feed field learnings back into the product.

Qualifications

• Hands-on hardware and software troubleshooting experience, ideally with microcomputers, embedded devices, cameras, or similar single-board computers.

• Comfort with Linux system administration: installing distributions, package management, systemd services, file permissions, and basic shell navigation.

• Working knowledge of Bash (and ideally Python) for reading and running simple diagnostic scripts and automating routine tasks.

• Solid networking fundamentals: TCP/IP, subnets, DNS, DHCP, basic firewall rules, and fluency with tools like ping, traceroute, tcpdump, and ssh.

• Strong customer-facing communication skills and the self-direction to operate independently onsite while staying tightly coordinated with a remote HQ team.

• Prior experience in a field service, forward deployed, or solutions engineering role is a plus.

• Familiarity with DevOps and software infrastructure tools such as Docker, Ansible, Portainer, etc. is a plus.

• Familiarity with computer vision systems, IP cameras, or industrial IoT deployments is a plus.

• Experience with Git, basic scripting in Python, or remote device management tools is a plus.