Prognostics and Diagnostics Engineer

PARC, a Xerox company, is in the Business of Breakthroughs. Practicing open innovation, we provide custom R&D services, technology, expertise, best practices, and intellectual property to Fortune 500 and Global 1000 companies, startups, and government agencies and partners. We create new business options, accelerate time to market, augment internal capabilities, and reduce risk for our clients.

PARC is incubating a new software venture in the Industrial Internet of Things (IIoT) space, based on industry-leading technology developed at PARC. Building on a world-class group of scientists and engineers with decades of experience in system health monitoring, the new venture has ambitions to redefine how industrial equipment is managed.

Job Description

We are looking for a Prognostics & Diagnostics Engineer who will be responsible for developing methods and models for anomaly detection, diagnostics, and prognostics of chemical process or plant equipment failure using streaming sensor data from industrial equipment as input. Reporting to the Chief Science Officer, the Prognostics & Diagnostics Engineer will develop mathematical models of chemical processes for real-time parameter estimation and process optimization.

In this role, the Prognostics & Diagnostics Engineer is expected to interact with clients in the chemical (pharma/O&G/process…) industry to understand their operational issues, formulate potential solutions, implement novel tools to address client concerns, and oversee deployment and commissioning of these solutions at process plants. He/she will bring the ability to work in a multi-disciplinary team of Mechanical and Chemical engineers, Computer Scientists, and algorithm designers, and experience in developing algorithms for production environments.

Responsibilities

1. Collect, clean, and analyze historical and new data from industrial equipment.
2. Identify needs for additional data collection and sensor deployment, including selection and placement of suitable sensors.
3. Build end-to-end production algorithms for asset anomaly detection, diagnostics, prognostics, and process optimization.
4. Build models that represent equipment behaviors under nominal conditions and different degradation modes.
5. Build reproducible tests for proposed models/algorithms.
6. Come up with creative ways to find and use algorithms that significantly impact performance metrics.
7. Work in close collaboration with software engineering to deliver production-grade code ready for industrial implementation.

Requirements

1. Advanced degree (Ph.D. preferred) in Engineering (Chemical, Mechanical, Electrical, …), Applied Physics, Computer Engineering or similar from a recognized university.
2. 5+ years of experience working as a Process Engineer designing, developing, and troubleshooting chemical processes.
3. Experience as a contributor on a range of projects – track record of delivering mature component degradation models and algorithms.
4. Excellent communication skills – must be able to articulate analysis and methodologies clearly and communicate insights in an accessible way to the team.
5. Must be able to conceive of solutions that have not been already defined.
6. Ability to program in Python with a good understanding of OOP.
7. Experience working with large real-time data streams.

Preferred Skills

1. Experience in CFD and/or FEA.
2. Hands-on plant experience working with technicians, operators, and engineers in a manufacturing setting.
3. Experience in modeling transport phenomena (heat and mass transfer).
4. Experience in developing digital twins for chemical processing unit operations.

The primary job location is Palo Alto, CA. Please note that the position will require occasional travel (up to 20%), mostly within North America. Remote work (including East Coast or Midwest locations) is negotiable for experienced candidates with demonstrated skills in managing complex projects without direct supervision.