Top Tech Jobs & Startup Jobs

Leads software quality assurance for embedded vehicle controllers, developing test plans, test cases, and continuous automation using Agile and BDD methods. Executes functional, safety, compliance, software-in-the-loop, hardware-in-the-loop, and vehicle testing; identifies defects and performance issues; mentors team members; improves quality processes; and collaborates with controls, diagnostic, software, and stakeholder teams to establish acceptance criteria.

Designs, documents, and implements scalable, low-latency C++ software on Linux-based systems for autonomous vehicles. Develops interfaces connecting the autonomy stack with sensors and custom vehicle hardware, while improving reliability through requirements generation, continuous integration, automated testing, issue tracking, and code reviews. Collaborates across teams, mentors developers, and delivers complex projects incrementally.

Own and develop GM’s global vehicle mass engineering systems and tools, including NGVMC, GPDS, THERA, and the Mass Book Tool. Support mass target setting, regression modeling, execution-phase tracking, certification workflows, and compliance reporting. Partner with IT and global engineering teams to ensure data integrity, system reliability, and process continuity. Explore AI, machine learning, analytics, and automation opportunities, while creating training materials, resolving escalations, documenting processes, and mentoring junior engineers.

Leads performance engineering for scalable backend services, APIs, microservices, and distributed systems. Diagnoses production performance issues, identifies bottlenecks, develops optimization strategies, and conducts load and capacity testing. Collaborates with DevOps, SRE, architects, and engineering teams on resilience, architecture, and technical design. Mentors junior engineers and drives performance best practices.

Develop autonomy evaluation metrics, statistical and machine-learning analyses, dashboards, and pipelines for simulation and on-road autonomous vehicle testing. Analyze perception, prediction, and planning performance; identify anomalous behavior and critical scenarios; apply VLMs and LLMs where appropriate; and support release gating and safety decisions. The role requires production Python, C++ debugging, technical leadership, cross-functional collaboration, and rigorous software engineering practices.

Leads global commodity strategy, sourcing, procurement, supplier negotiations, contracts, cost reduction, capacity planning, and supply resilience. Manages global teams, develops employees, collaborates cross-functionally, oversees supplier relationships, and executes procurement budgets and business plans. The role requires 10–20% domestic and international travel and regular hybrid attendance in Warren, Michigan.

Architect and build evaluation metrics, statistical and ML analyses, dashboards, and pipelines for autonomous driving systems. Analyze simulation and on-road time-series data, evaluate perception, prediction, and planning models, identify anomalous behavior, and support release-gating and safety decisions. The role requires production Python development, C++ codebase work, cross-team technical leadership, and integration of advanced AI models for scenario classification and validation prioritization.

Lead and support ATW projects for ICE propulsion controls: define requirements, develop controller software and calibrations, verify on SIL/HIL, engine carts, dyno or vehicles, and perform emissions testing to meet regulatory and performance targets.

Define architecture and metrics for autonomous driving evaluation, lead cross-functional integration across autonomy and simulation teams, develop statistical and machine learning methods, analyze large-scale time-series data, manage evaluation KPIs and release gates, and communicate safety and readiness insights through dashboards and stakeholder presentations.

Develop scalable backend services, APIs, event-driven workflows, metadata pipelines, configuration tools, deployment controls, and observability for vehicle data collection across fleets. The role owns production systems, improves data quality and campaign monitoring, leads cross-team technical initiatives, and contributes through architecture reviews, testing, code reviews, mentorship, and production support. Collaboration spans AI research, data engineering, vehicle engineering, autonomy, privacy, product, and operations teams.