Top Tech Jobs & Startup Jobs

Provides senior technical leadership for automated automotive body shop controls systems. Leads PLC, robotics, welding, material handling, network architecture, equipment upgrades, capital projects, troubleshooting, reliability, safety, continuous improvement, and production launches. Mentors engineering and skilled-trades teams, coordinates with plant leadership and suppliers, manages project schedules and budgets, and supports second-shift operations and critical production periods.

Leads the strategy, validation, and safety assurance of Level 3–4 autonomous driving behaviors powered by machine learning. Owns behavior-related safety cases, standards alignment, ODD and evaluation frameworks, safety metrics, launch-readiness assurance, and evidence assessment across simulation, closed-course, and public-road testing. Leads cross-functional technical collaboration and builds a high-performing AV behavior safety engineering team through hiring, coaching, and development.

Own numerical analysis and model parity for compressed, quantized, and optimized autonomous-vehicle models. Develop Jacobian/Hessian sensitivity tools, connect numerical differences to driving behavior, diagnose training instabilities, and build low-overhead observability for distributed training. Investigate floating-point errors, edge cases, and implementation divergence while translating analytical results into deployment decisions and production-ready tooling.

Leads development and release planning for embedded control products, coordinating software, calibration, hardware, validation, suppliers, and vehicle program stakeholders. Serves as integration manager and customer interface, tracks deliverables, manages team backlog, leads engineering meetings, and provides technical direction and issue resolution. Requires extensive real-time embedded software, controls, AUTOSAR, automotive product lifecycle, vehicle architecture, calibration, integration testing, and validation experience.

Design, architect, deploy, and optimize advanced machine learning models for real-time onboard autonomous driving. Lead end-to-end ML projects, improve neural architectures and inference performance, ensure robustness and safety in critical systems, mentor engineers, collaborate across engineering teams, and influence technical roadmaps. The role focuses on foundation models, computer vision, sensor-to-action learning, and onboard autonomy.

Designs, develops, and implements thermal management control and diagnostic algorithms for next-generation electric vehicles. Responsibilities include developing embedded software in C and Simulink, interpreting functional requirements, creating unit and multicomponent tests, integrating ECU software, and performing SIL and HIL testing. The role collaborates with multidisciplinary engineering teams and requires 10% domestic and international travel, with a hybrid schedule requiring three days in the office.

Executes manual and automated testing for automotive infotainment systems, configures embedded test benches, documents defects, develops test cases and automation scripts, and supports build promotions and issue escalation. Collaborates with engineering teams on defect resolution and tests Android-based embedded applications using CI/CD pipelines, Jenkins, automotive communication protocols, and Python, Java, or Kotlin.

Leads supplier automation assessments and maturity strategies across manufacturing environments. Evaluates material handling and flow systems, develops improvement plans, supports sourcing and negotiations, and coordinates suppliers with industrialization, purchasing, and program teams. Owns automation evaluation processes, presents recommendations to senior leadership, and drives cross-functional adoption. Requires manufacturing or automation experience, strong analytical and stakeholder-influence skills, and regular domestic and international travel.

Build and maintain master data, metadata, repositories, logical data models, and data standards. Assemble complex datasets, improve data processes and infrastructure scalability, and develop industrialized analytical datasets and delivery mechanisms. Use data pipelines to generate insights into customer acquisition, operational efficiency, and business performance metrics. This is a hybrid role requiring three days in the office and two days remotely.

Develop software, frameworks, data pipelines, and quantitative methods to measure confidence in autonomous vehicle validation. Analyze simulation and real-world test data, evaluate coverage and predictive validity, detect regressions, define metrics and decision criteria, and improve validation workflows. The role requires collaboration across simulation, safety, autonomy, and release teams to support risk, readiness, and release decisions with defensible evidence.