- Location
- San Francisco, California, United States
- Workplace
- Remote, Onsite
- Department
- Engineering & Technology
- Seniority
- Manager
- Education
- PhD
- Source
- Greenhouse
Description
About Redwood Materials
Redwood Materials was founded in 2017 by JB Straubel, co-founder and former CTO of Tesla, on a simple but radical idea: the critical minerals powering the energy transition already exist. They just need to come back. Today Redwood is the largest lithium-ion battery recycler in North America — recovering, refining, and redeploying critical minerals from end-of-life batteries back into the supply chain. On the energy side, Redwood has deployed the largest second-life battery project in the world, delivering power to AI data centers in months rather than years using proprietary energy architecture engineered entirely in-house. The company is profitable, the market it operates in is projected to grow 20 to 50 times over the next decade, and Redwood is the only company with the supply chain, the technology, and the operational scale to lead it.
Position Summary:
At Redwood Materials, we are moving beyond battery recycling to build the most advanced, circular energy ecosystem on the planet—shifting the industry from static, hardware-heavy infrastructure toward agile, software-defined energy assets. The Software Test and Validation organization is the ultimate gatekeeper of quality, reliability, and operational readiness across our entire hardware and software portfolio.
As the Senior Manager for Software Test & Validation, you will build and lead the engineering teams responsible for four mission-critical pillars: Power Electronics and Site-Level SIL/HIL Simulation, Manufacturing Test Software, Site Commissioning Tooling, and Fleet Data Analytics for Preventive & Predictive Maintenance. You are the bridge between pure code, factory production, and long-term grid reliability. We are looking for a hands-on technical leader who can architect high-fidelity real-time simulation plants, scalable factory test frameworks, and predictive fleet health models alongside their engineers—driving quality across multiple concurrent hardware programs from R&D bring-up through volume manufacturing and multi-year field operations.
This position is based in our San Francisco office and operates on an onsite work model.
Essential Duties and Responsibilities
Multi-Level SIL & HIL Validation Architecture
- Power Electronics & Site-Level Simulation: Direct the architecture and scaling of our Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) infrastructure (Typhoon HIL, Opal-RT) across both sub-microsecond power conversion stages and multi-asset, site-level controllers.
- Custom HIL Hardware & Plant Modeling: Oversee the design of custom signal-conditioning interface hardware, fault-injection panels, and high-fidelity virtual plant models (battery arrays, resonant DC/DC and multi-level AC/DC converters, and dynamic grid conditions) to stress-test embedded firmware and site software before field deployment.
- Continuous Verification & CI/CD: Integrate automated SIL and HIL regression suites into containerized CI/CD pipelines (GitHub Actions/Jenkins, Docker), serving as the definitive release gate for all production-bound embedded Rust, C/C++, and site-level software.
Manufacturing Software & Factory Test
- Production Line Software: Lead the development of automated manufacturing test software and end-of-line (EOL) functional test frameworks for multiple Redwood hardware product lines, including our custom Power Conversion Systems (PCS) and energy storage enclosures.
- Factory-to-Engineering Integration: Build reliable firmware flashing, hardware calibration, serialization, and automated pass/fail diagnostics systems that scale from low-volume prototype builds (EVT/DVT) to high-volume factory production.
Site Commissioning & Predictive Fleet Analytics
- Commissioning Tooling: Architect and deliver intuitive, automated field commissioning tools that streamline site bring-up, verify hardware-software wiring and communications (CAN, Modbus TCP, Ethernet, SPI), and execute automated site acceptance testing (SAT) for new energy storage deployments.
- Preventive & Predictive Maintenance Analytics: Lead the architecture of fleet-wide data analytics frameworks and time-series observability pipelines (e.g., InfluxDB, Prometheus, Grafana, Python) that ingest continuous telemetry from deployed field assets to drive preventive and predictive maintenance.
- Prognostics & Early Fault Detection: Develop automated health-monitoring models and anomaly detection algorithms that track thermal drift, component degradation, switching efficiency shifts, and battery state-of-health (SoH) trends—flagging incipient hardware or control issues for proactive servicing before they cause unplanned downtime.
Leadership & Organization Building
- Team Growth & Technical Mentorship: Recruit, mentor, and lead a multidisciplinary team of validation, test automation, manufacturing software, and data/reliability engineers; foster an engineering culture obsessed with breaking complex state machines and catching failure modes early.
- Cross-Functional Execution: Partner closely with Power Electronics Controls, Embedded Firmware, Hardware Engineering, Manufacturing Operations, and Field Service teams to close the loop between factory test signatures, HIL models, and real-world predictive maintenance actions.
Skills, Knowledge, and Abilities
Qualifications
- Education & Experience: MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field (or BS with equivalent elite depth), combined with 10+ years of industry experience in software validation, HIL simulation, manufacturing test, and fleet reliability analytics for complex hardware systems, and 5+ years leading technical engineering teams.
- SIL/HIL & Power Systems Mastery: Proven track record architecting real-time simulation environments (Typhoon HIL, Opal-RT, or dSPACE) for both high-frequency power electronics converters and distributed system/site controllers.
- Manufacturing & Commissioning Software: Demonstrated experience building and deploying automated factory test software (ICT/FCT/EOL), hardware bring-up utilities, and field commissioning frameworks across multiple hardware product lifecycles.
- Predictive Analytics & Software Toolchain: Expert-level proficiency in Python (Pytest, Pandas, SciPy, time-series and predictive modeling stacks) for test automation and fleet prognostics, alongside solid working fluency in Rust and C/C++ to inspect, instrument, and debug low-level firmware and application codebases.
-
- Data Infrastructure & DevOps: Strong experience designing automated CI/CD pipelines for hardware-in-the-loop targets, containerization (Docker), and scalable time-series telemetry architectures for fleet health monitoring and predictive maintenance.
- Hardware & Lab Fluency: Deep comfort operating in high-voltage power electronics lab environments, utilizing oscilloscopes, logic analyzers, power analyzers, and industrial communication protocols (CAN/CAN-FD, Ethernet, Modbus, SPI) to isolate elusive hardware-software interactions.
Bonus Qualifications
- Experience validating grid-scale Battery Energy Storage Systems (BESS), utility-interactive inverters, or mixed-chemistry/second-life EV battery installations against UL 1741, UL 1973, and IEEE 1547 standards.
- Proven experience building prognostic algorithms that correlate factory EOL baseline signatures with in-field operational telemetry to predict remaining useful life (RUL) of power electronics or energy storage components.
- Track record of designing custom automated fault-injection hardware and custom breakout PCB interfaces for multi-rack HIL testbeds.
In accordance with California pay transparency laws, the salary range for this position is listed below. Actual compensation may vary based on a variety of factors, including experience, education, and skills.
The position is full-time. Compensation will be commensurate with experience.
We collect personal information (PI) from you in connection with your application for employment with Redwood Materials, including the following categories of PI: identifiers, personal records, professional or employment information, and inferences drawn from your PI. We collect your PI for our purposes, including performing services and operations related to your potential employment. If you have additional privacy-related questions, please contact us at [email protected].