Jobs / United States / Path Robotics INC

Path Robotics INC

Staff Mechanical Engineer, Technical Lead

Columbus, Ohio Posted today

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Skills this job asks for

WeldingLeadershipProduct managementMachine learning

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 18 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Path Robotics INC paid sponsored hires in similar roles1 certified filing for “Robotic Software Reliability Engineer” (Mechanical Engineers) in OH: $145k–$145k, median $145k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 18 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Path Robotics INC paid sponsored hires in similar roles
1 certified filing for “Robotic Software Reliability Engineer” (Mechanical Engineers) in OH: $145k–$145k, median $145k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

Build the Path Forward At Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use. Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together We're looking for a Technical Lead to guide our team's contribution to Path's manipulation products as we expand from autonomous welding into factory automation. On our Sensing and Embodied Intelligence team, you'll set direction for sensing end-of-arm tooling, the physical interfaces between robots, tools, sensors, and parts, and the tasks we design to train manipulation models. This is a hands-on leadership role. You'll define architecture, make the hard tradeoff calls and build hardware yourself. What You'll Do Technical Direction • Own the technical roadmap for sensing end-of-arm tooling, physical interfaces, and training task design • Translate product goals and model training needs into hardware requirements and interface specifications • Lead design reviews and set standards for robustness, serviceability, and manufacturability • Identify technical risks early and retire them before they reach the field Sensing End-of-Arm Tooling • Lead the design of end-of-arm tooling that integrates cameras, 3D, force/torque, tactile, and proximity sensors • Define sensor placement, calibration, and mounting that hold accuracy under vibration, heat, spatter, dust, and repeated contact • Drive tooling from concept through production release Physical Interfaces • Define mechanical, electrical, and data interfaces between robots, tools, tool changers, sensors, fixtures, and workpieces • Establish standards that let tools and sensors be swapped, serviced, and reused across platforms • Align physical interfaces with hardware abstraction, calibration, and control architecture Task Design for Model Training • Design the tasks, fixtures, parts, and environments used to collect demonstration and training data • Define task variation, difficulty, and success criteria that represent real industrial work • Partner with ML engineers to connect task design to model performance How You Deliver • Own the full lifecycle — requirements, design, prototyping, validation, deployment, and improvement • Align hardware with product goals across mechanical, electrical, software, and ML teams • Mentor engineers and build sound engineering judgment across the team • Work with vendors, suppliers, and our shop to turn designs into hardware — fast • Drive root cause analysis and design improvements from field and reliability data What We're Looking For • Degree in Mechanical Engineering, Mechatronics, Robotics, or a related field, or equivalent experience • 7+ years in robotics, automation, or industrial hardware development, with systems deployed in the real world • A track record leading the technical direction of a hardware product or subsystem from concept through deployment • Deep experience designing end-of-arm tooling, grippers, or sensor-integrated robotic payloads • Strong grasp of how mechanical design affects sensor calibration and performance • Experience defining interfaces in electromechanical systems: connectors, cabling, tool changers, and communication protocols • Familiarity with imitation or demonstration-based learning and how data collection design affects model results • Proficiency in SolidWorks or equivalent CAD with PDM-based release workflows Why You’ll Love W

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