MicroVision, a pioneering company in MEMS-based laser beam scanning technology, is seeking a Staff Software Engineer specializing in deterministic machine learning algorithms at their Redmond, WA location. This role offers a competitive salary range of $160,000 – $200,000 and is part of their innovative automotive LiDAR product development team.
The position requires a unique combination of machine learning expertise and software engineering skills, with a focus on developing algorithms that can be mathematically or statistically verified for deterministic behavior. The ideal candidate will have at least 4 years of relevant experience or a Ph.D. in a related field, along with strong foundations in digital signal processing, linear algebra, geometry, and probabilistic theory.
As a key member of the Software Engineering team, you'll be responsible for designing and implementing machine learning algorithms with verifiable mathematical proofs, testing models for consistency and accuracy, and ensuring reliable performance in real-world applications. The role involves close collaboration with cross-functional teams and adherence to ASPICE and ISO26262 best practices.
MicroVision offers an attractive benefits package including comprehensive medical and dental plans, vision coverage, 401k with company match, flexible vacation policy, and parental leave. The company maintains a hybrid work model, requiring employees to live within commuting distance of the Redmond headquarters.
This position represents an opportunity to work at the intersection of cutting-edge technologies including MEMS, lasers, optics, and machine learning, specifically focused on automotive ADAS applications and industrial solutions. The role offers the chance to make significant contributions to market-defining products while working with a diverse team of technical experts.
For candidates passionate about deterministic machine learning and its applications in automotive technology, this role provides an excellent opportunity to work on innovative solutions that will shape the future of ADAS and autonomous systems.