WellNest

Compensation

Full Description

We are looking for a senior mmWave radar algorithms engineer with deep, hands-on experience with Texas Instruments mmWave radar SoCs, to own our radar perception stack end-to-end. This role is central to our product and will directly shape chip selection, system architecture, and the technical roadmap. This position is algorithm- and deployment-driven. Strong familiarity with TI mmWave chips, SDKs, and real-world constraints is mandatory. What you’ll do • Own the design and implementation of mmWave radar perception pipelines for object and weapon detection, from raw ADC data through detection, tracking, and classification • Lead TI mmWave chip selection and roadmap planning, advising on the right SoCs (AWR / IWR / xWR families) based on performance, power, cost, and product timelines • Develop and optimize real-time FMCW / MIMO radar signal processing chains deployed on embedded TI hardware • Build and deploy multi-target tracking systems using advanced estimation techniques (Kalman filtering, JPDA, IMM, EKF/CKF) • Design algorithms that fundamentally reduce false alarms in cluttered, real-world environments • Own bit-exact Matlab ↔ C/C++ frameworks and validate on-device implementations against algorithmic models • Develop internal tooling for radar data capture, calibration, visualization, and labeling, enabling rapid iteration and model training • Collaborate closely with systems, product, and hardware teams to translate sensing requirements into production-ready radar solutions Required background (non-negotiable) • Strong, hands-on experience with Texas Instruments mmWave radar SoCs and SDKs • Deep expertise in mmWave radar signal processing: FMCW, MIMO, DOA, SAR/ISAR, near-field processing • Proven experience shipping real-time radar algorithms on embedded systems under strict latency, power, and memory constraints • Expert-level C/C++ and Matlab (Python a plus) • Strong foundation in tracking, estimation, and sensor fusion (radar-first, camera optional) • Ability to own problems end-to-end, from algorithm design through deployed, validated code Highly valued experience • Prior ownership of TI radar algorithm stacks, SDK demos, or reference designs • Experience contributing to or maintaining radar algorithm repositories used by multiple customers or products • Development of object classification pipelines for radar (traditional or ML-based) and deployment on TI mmWave devices • Multi-sensor synchronization and fusion (radar + camera + IMU / odometry) • Background in security sensing, automotive radar, robotics, or defense-related perception systems One-line internal framing This role owns TI mmWave chip selection, radar algorithms, and the perception roadmap for real-time object and weapon detection.