Technical Engineering Manager, Physical AI Solutions (UR & MiR, North Reading, MA)
Teradyne · North Reading, MA
- Level
- Manager
- Team
- Manufacturing
- Base pay
- $220k–$352k
- Industry
- Industrial
- Posted
- Recently
The role in 30 seconds
A management manufacturing role at Teradyne (industrial) in North Reading, MA. Be responsible for taking AI innovations from concept through production deployment and ongoing customer support.
- Tools it names
- Robotics, Automation
- Base pay
- $220k–$352k
Read from the posting. The full description is below.
From the plant jobs report · week of November 2, 2026
Manufacturing Engineer roles in Massachusetts: typical posted base $103k–$152k. This one lists $220k–$352k.
Median of the low and high ends of 47 live postings that list pay, out of 83 manufacturing engineer openings in Massachusetts, read from manufacturers' own careers sites.
Massachusetts plant jobs report →Pay by team and state →What moves pay →
How this role compares
Against 82 other live manufacturing postings in Massachusetts.
- Base pay
- About 137% above similar roles
- Experience asked
- Not stated
Typical $96k–$145k, from 38 postings that list pay.
Similar roles usually ask 7+ years.
Skills these teams ask for most
- ✓ Automation 55%
- Tooling 49%
- Lean 47%
- ✓ New product launch 33%
- Root cause 33%
- Six Sigma 33%
✓ = this posting asks for it too. % = share of similar postings that mention it.
At a glance
Pulled from the posting text. If it's not listed here, the posting didn't say.
How to get in at this plant
Five moves over a week or two. The first one takes ten minutes.
- 1
Pick 2–3 people on the Manufacturing team at Teradyne
Engineers who joined in the last year or two reply the most. Use the team search on this page to find them.
- 2
Send a short, curious note
One real question about their work. No favors yet. Each person gets a different note, written for this role.
- 3
Turn a reply into a short call
Questions worth asking about this team:
- What does a normal week look like on your team?
- Is the work mostly new product launches or sustaining existing lines?
- How much time do you spend on the floor versus at a desk?
- How did you land the job? What stood out in your interviews?
- 4
Apply with someone vouching for you
If the call went well, ask whether they’d pass your résumé to the hiring manager. Send your résumé link, apply that day, and let them know.
- 5
Bring proof to the interview
One page of before-and-after numbers from projects you led: scrap, OEE, cycle time, cost. Plant managers hire on results.
This plant: Teradyne in North Reading
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Full description from TeradyneAs posted on their careers site.ShowHide
requirements
and performance trade-offs
- ✓Ensure robust integration of AI functionality into existing robotic software stacks
- ✓Guide data science and engineering efforts recognizing that high-quality training and evaluation data is fundamental to successful AI/ML solutions
requirements
of industrial environments
- ✓Balance cutting-edge innovation with practical engineering constraints
Show full description ↓Show less ↑
Our Purpose
TERADYNE , where experience meets innovation and driving excellence in every connection. We are fueled by creativity and diversity of thought and in our workforce. Our employees are supported to innovate and learn something new every day.
We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results
Opportunity Overview
We're seeking a Technical Engineering Manager to lead a team of AI engineers focused on developing and deploying physical AI robotic solutions in industrial automation. This role sits at the intersection of cutting-edge AI technology and practical product engineering, requiring someone who can balance innovation with the reliability demands of our customers.
You'll lead a team responsible for the development and deployment of physical AI capabilities that enable robots to navigate, manipulate, and interact with their environments with unprecedented intelligence. This includes advancing our work in obstacle detection, object identification and classification, pose estimation, SLAM, and precision localization systems leveraging AI and ML technologies. You’ll have the opportunity to work in both the autonomous mobile robots (AMRs) and collaborative robot arms (cobots) space.
This position requires strong technical expertise combined with proven leadership abilities to guide your team through the complete development lifecycle—from concept to customer deployment.
Our team is building differentiating solutions that push the boundaries of what robots can perceive, understand, and interact with in dynamic real-world environments. You'll work alongside world-class engineers to deliver full-stack AI solutions that don't just work in simulation—they thrive in our customers' facilities.
Teradyne Robotics is transforming industrial automation through intelligent robotic solutions. Our portfolio includes Universal Robots (UR), the global leader in collaborative cobots, and Mobile Industrial Robots (MiR), pioneers in autonomous mobile robots. Together, we're building the future of flexible, intelligent automation for manufacturing and logistics environments worldwide.
You'll lead the development and deployment of physical AI capabilities that enable robots to navigate, manipulate, and interact with their environments with unprecedented intelligence. This includes advancing our work in obstacle detection, object identification and classification, pose estimation, SLAM technologies, and precision localization systems.
Working across our platform for simulation and data generation, you'll help engineer solutions that leverage diverse sensor modalities—from RGBD cameras and LiDAR to Time-of-Flight sensors—making informed trade-offs based on performance, cost, and application requirements. You'll be responsible for taking AI innovations from concept through production deployment and ongoing customer support.
All About You
Technical Leadership
- •Lead the development of physical AI solutions including obstacle detection, object identification and classification, pose estimation, SLAM technologies and localization systems.
- •Develop and leverage simulation (leveraging NVidia's Issac Sim and Cosmos) as a tool to aid engineering, training data generation and test development.
- •Drive technical decisions around sensor selection and integration (RGBD cameras, LiDAR, ToF sensors, and more) based on application
Team Management
- •Manage and develop a team of AI engineers, providing technical mentorship and career guidance
- •Foster a collaborative team environment focused on delivering full-stack solutions, not just isolated algorithms
- •Build team capabilities through hiring, training, and continuous skill development
- •Promote engineering excellence and best practices across the team
Product Delivery
- •Take ownership of features from conception through market launch and post-deployment customer support
- •Apply project management skills to plan, track progress, identify risks, and ensure successful execution
- •Ensure solutions meet the reliability and robustness
Cross-Functional Collaboration
- •Work closely with R&D teams at Universal Robots and Mobile Industrial Robots
- •Collaborate with hardware, software, product management, and customer success teams
- •Communicate technical concepts and progress effectively to both technical and non-technical stakeholders
- •Contribute to the broader technical strategy for physical AI across the organization
Technical Expertise
- •Sensor Technologies: Deep understanding of different sensor types (RGBD cameras, LiDAR, Time-of-Flight sensors, etc.) and the practical trade-offs between them in robotic applications
- •Simulation Experience: Proven track record utilizing simulation to support engineering development and testing efforts
- •Physical AI Domain Knowledge: Hands-on experience with concepts including:
- •Obstacle detection and avoidance
- •Object identification and classification
- •Pose estimation techniques
- •SLAM technologies (visual, LiDAR, multi-sensor fusion)
- •Global and relative localization methods
- •Experience with both AI components from open source and academia in addition to NVIDIA Isaac platform
- •Familiarity with Vision-Language-Action (VLA) models and their potential applications in robotics
- •Experience building and managing data pipelines at scale for ML applications
Software E
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