oneNav is powering high-performance positioning for location-dependent mobile services. Based in Silicon Valley, oneNav is developing a next-generation, pureL5TM mobile GNSS receiver for smartphones, wearables, and IOT devices. Bring your best GNSS and embedded SW programming skills and get hands-on with the application of modern Machine Learning methods to GNSS!
This position is focused on leading the team responsible for delivering the world’s first commercial real-time embedded positioning engine (PE) for a pureL5TM GNSS receiver. The oneNav PE is comprised of a Position Manager (PM) that supervises the interactions between the firmware-based Measurement Engine (ME) firmware (which, in turn, exercises an array processor custom-designed as an IP core to harness the unique attributes of the GNSS L5 signal structure) and embedded software-based Position Engine (PE). The PE features classic PE approaches together with groundbreaking Machine Learning (ML) methods that dramatically improve horizontal accuracy even in the most challenging environments.
- Contribute to the delivery of timely, commercial, portable, real-time embedded C/C++ PE software in support of the one Nav GNSS Receiver IP core product
- Work closely with world-class experienced GNSS technical to implement novel applied R&D projects that combine classic PE approaches (WLS, RANSAC, UKF) with advanced ML techniques to leap-frog performance in the areas of geometric visibility of satellites, multipath estimation, and position estimation, including classification and regression using CNN, RNN, and ensembles of mixed architectures
- Generate code consistent with SW development practices aligned with DevOps principles and implemented in a CI/CD workflow
- 2-5 years with embedded SW development for commercial products for mobile wireless, IoT, and GNSS
- 2-5 years hands-on real-time embedded SW development with RTOS on ARM or RISC-V
- Exposure to with GNSS receiver design, including GNSS Modernized Signals (e.g., L5)
- Exposure to multi-constellation GNSS PE designs, including inter-system challenges
- Exposure to Autonomous, Assisted GNSS with LTO, and Assisted GNSS modes
- Exposure to implementing PE classic methods: WLS, RANSAC, UKF
- Exposure to implementing PE-based methods for multipath identification and mitigation
- Exposure to modern Machine Learning methods, such as CNN, RNN, LSTM, etc.
- Commitment to solid SW development process, including coding conventions, code reviews, unit-testing, QA, and system integration
- Commitment to DevOps and Continuous Improvement/Continuous Development
- Excellent written and verbal communication skills
- Comfortable working in focused fast-moving start-up environment
- BS and MS, or PhD in EE, CS, Math, or equivalent foundational technical subject
About the Team:
oneNav’s team comprises top GNSS experts from Qualcomm, Apple, Intel, SnapTrack, SiRF and Trimble, with decades of GNSS and mobile industry experience. Our team has extensive experience in GNSS system architecture, multipath, signal processing, ASIC design and AI/machine learning, and has collectively filed over 200 career GNSS patents. We are backed by Norwest Ventures, GSR Ventures and Google Ventures. You can find more information at www.onenav.ai.