Jobs at General Motors

Design, build, and operate governed feature engineering platforms and scalable pipelines supporting machine learning development and production inference. Develop feature transformations with Python, SQL, Spark, and Databricks; maintain feature stores, data quality controls, CI/CD, monitoring, lineage, and train-serve parity. Collaborate with data scientists, ML engineers, data engineers, and platform teams to deliver reliable, reusable production features.

Develop data-centric machine learning systems for autonomous driving. Design dataset mixtures, curation, mining, sampling, evaluation, and scaling-law experiments; train foundation models using real and synthetic driving data; investigate failures and improve data quality. Apply self-supervised, imitation, and reinforcement learning to perception and trajectory generation. Collaborate on large-scale multi-GPU training, production deployment, and integration into onboard driving systems.

Serves as the senior technical authority and system architect for GM’s physical and virtual test platform ecosystem. Defines long-term architecture, roadmaps, APIs, interfaces, ownership boundaries, and AI strategy across test, simulation, automation, infrastructure, and operations. Leads complex investigations, drives cross-functional technical decisions, mentors senior engineers, and improves platform reuse, reliability, scalability, throughput, asset readiness, and adoption.

Leads a 15-person engineering organization building scalable, multi-site compute infrastructure for automotive test and simulation benches. Owns technical direction, platform roadmap, reliability, capacity and investment planning, observability, security, production readiness, and customer enablement. The role coordinates engineering, IT, networking, security, and test-program stakeholders while scaling infrastructure beyond 500 benches and developing engineering leadership.

Build and operate GM’s internal cloud platform, including self-service infrastructure, APIs, CLI and MCP tools, Kubernetes runtime capabilities, multi-region reliability, and automated delivery workflows. Define technical direction, eliminate developer toil, establish golden paths, improve SLOs and observability, partner with SRE on incidents, mentor engineers, and collaborate with application teams to improve developer experience.

Staff software engineer responsible for designing, building, and operating production authorization services. The role develops role-based, attribute-based, and policy-driven access controls; leads security reviews; builds cloud-native microservices and APIs; establishes engineering standards, observability, and deployment practices; mentors engineers; and supports critical systems through on-call rotations.

Build and operate production software, backend services, data pipelines, infrastructure, and workflow automation for autonomous vehicle simulation testing. Automate test creation, execution, validation, monitoring, and maintenance while integrating evaluation systems and partner tools. Lead technical design, code reviews, architecture, and cross-functional execution across autonomy, safety, systems, data, and infrastructure teams. Improve reliability, observability, quality, and scalability of simulation testing through cloud-native engineering and analytics.

Lead the architecture and long-term roadmap for GM’s vehicle Core OS platform, including hypervisors, virtualization, safety partitioning, boot and secure boot, container runtimes, and workload orchestration. Define multi-OS platform interfaces across Linux, Android, and QNX; drive performance, reliability, and safety strategies; guide technology selection and supplier relationships; mentor senior engineers; and lead complex cross-functional investigations and architecture decisions.

Lead the architecture and development of GM’s vehicle Core OS virtualization platform. Build hypervisor capabilities, guest OS enablement, secure boot, container runtime, resource governance, health monitoring, and fault recovery across embedded Linux, Android, and QNX. Optimize and debug system performance across hardware and software boundaries, establish CI/CD and HIL validation, and mentor engineers while collaborating with safety, cybersecurity, BSP, and silicon teams.

Leads domestic relocation and Global Mobility program operations, governance, policy development, vendor management, complex case resolution, and continuous improvement. Advises HR, business leaders, employees, and service providers; analyzes data and market benchmarks; develops implementation plans and recommendations; manages escalations; and drives modernization, process redesign, technology enhancements, and stakeholder experience improvements.

Manage government accounts across Texas, Oklahoma, Louisiana, and Mississippi; develop sales strategies, build agency relationships, influence procurement specifications, manage pipelines, forecast revenue, and drive customer adoption and account expansion. The field-based role requires frequent travel of up to 75%, residence or relocation to Dallas or Houston, a valid ability to operate a motor vehicle, and government B2G/B2B sales experience.

Design and implement AI agents, plugins, automations, and enterprise integrations for HR Technology platforms. Lead requirements gathering, technical analysis, solution design, testing, documentation, deployment, security, and data integrity efforts across HR, IT, and business stakeholders. Integrate platforms including ServiceNow, Workday, and other enterprise applications while supporting the HR automation and AI roadmap.

Leads Chevrolet sales and aftersales performance across a dealership zone. Builds dealer relationships, develops District Sales Managers, analyzes market and sales data, drives market share and profitability, oversees dealer compliance and digital marketing execution, manages inventory performance, and implements customer retention and business growth strategies. The role is field-based, requires frequent travel, and includes team coaching, dealer negotiations, and strategic planning.

Designs and develops IAM and security software, automation, APIs, and microservices. Integrates security into cloud and CI/CD environments, conducts code reviews and threat modeling, monitors security events, supports incident response, and advises teams on identity architecture and best practices. Requires extensive IAM administration, programming, cloud, containerization, and secure-coding experience.

Provides on-site automotive technical support to GM dealerships and wholesale teams. Diagnoses vehicle and Techline issues, resolves escalated cases, supports repair and repurchase prevention, reviews dealership service readiness, trains personnel, troubleshoots IT and diagnostic tools, and reports product concerns to GM engineering and quality teams. The role manages territory relationships, supports arbitration and legal cases, and requires frequent travel, extensive automotive diagnostic experience, and strong customer and technical communication skills.

Provides on-site automotive technical support to GM dealerships across the Albany territory. Diagnoses and directs vehicle repairs, resolves escalated technical and customer issues, supports warranty and repurchase reduction, evaluates dealership service readiness, trains dealer personnel, reviews comeback processes, and communicates product concerns to GM engineering and quality teams. The role also supports arbitration and legal cases, manages dispatch cases, develops dealer relationships, and assists with technician recruitment and retention.

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.

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 ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

The Technical Lead will architect and implement systems for data processing and testing workflows in the autonomous vehicle development space, optimize software engineering practices, and guide a team of engineers.