Process Controls Engineer, Sensing & DAQ
- Market p25–p75
- $120k–$165k
- Hadrian p25–p75
- $144k–$185kn=47
- Opened · 30d
- +16
- Closed · 30d
- −10
- Opened · 7d
- +3,86310% of open
- All software engineering
- 75,455open
Hadrian - Manufacturing the Future
Hadrian is building autonomous factories to reindustrialize America. By combining AI, advanced software, robotics, and full-stack manufacturing, we help aerospace and defense companies build rockets, satellites, aircraft, ships, and other mission-critical systems up to 10x faster and at significantly lower cost.
Following our $1.37B Series D at a $7.87B valuation, Hadrian is rapidly expanding our manufacturing footprint, launching new capabilities across welding, casting, forging, electronics, additive manufacturing, and more, while scaling our Factory-as-a-Service platform to transform how critical products are built.
Backed by leading investors including JPMorgan Chase, Valor Equity Partners, Andreessen Horowitz, Founders Fund, 137 Ventures, Lux Capital, T. Rowe Price, and Morgan Stanley, we’re building the future of American manufacturing—and looking for exceptional people to help make it happen.
If you’re ready to take on the most challenging and rewarding work of your career while helping create American manufacturing jobs for generations to come, you’re exactly who we’re looking for.
The Role
Applied Physical Systems is a small, cross-functional engineering team at Hadrian. We build technology that spans more than one manufacturing capability, needs hardware and software designed together, and can't be bought off the shelf. We take a solution from proof of concept through prototype to a first production-ready version, then hand it to the teams that run it at scale. Engineers on the team design, build and commission their own systems on the factory floor.
You will lead how Hadrian measures its machines and processes, from sensor selection to data that engineers can act on. Your time will split between designing acquisition hardware and software, instrumenting equipment on the factory floor, and analyzing the signals you collect. You will work with process and manufacturing engineers to learn which failures matter, with data and software teams on how process data is stored and used, and with controls engineers as the work moves toward closed-loop control.
What You’ll Do
Design vendor-agnostic data acquisition (DAQ) systems, covering sensors, signal conditioning, time base, edge compute, storage and APIs
Instrument manufacturing equipment and processes, and reuse the same platform across machines
Specify sensors, placement and front-end electronics against noise and bandwidth budgets
Synchronize process signals with robot and machine position and state
Build signal-processing pipelines that turn raw data into features and process state
Work with process engineering teams to turn failure modes into measurement requirements
Decide when COTS hardware is enough, and design or contract custom electronics when it is not
Develop monitoring and closed-loop control of physical processes
What We’re Looking For
Bachelor's degree in electrical, computer or mechanical engineering, physics, or a related field
Strong electrical fundamentals, including grounding, shielding and noise in measurement systems
Software engineering in Python and C or C++, including version control and testing
Control fundamentals, with experience in feedback control of a physical process
Experience selecting, placing and calibrating sensors across force, vibration, acoustic, optical, thermal and electrical measurements
Experience with digital signal processing, including filtering, spectral analysis and feature extraction
Experience designing multi-channel DAQ systems, including sampling, triggering and time synchronization
Experience writing embedded or real-time software on microcontrollers, FPGAs or real-time controllers
Comfort working on the factory floor with operators and process engineers to learn what needs measuring
Daily use of AI tools for analysis, firmware and documentation, with experience reviewing and verifying outputs for quality and completeness
What Will Set You Apart
Training and validating data-driven process models, such as anomaly detection or defect classifiers