General Motors

Manager

• Serve as the primary advocate and trusted advisor for OnStar
• Build strong, trust‑based relationships with dealer principals, general managers, sales leaders, and service leaders
• Act as the liaison between OnStar, GM vehicle brands, and your assigned dealerships
• Deliver impactful training – lead virtual sessions with dealer leadership and front‑line teams
• Confidently troubleshoot issues related to OnStar and internal platforms
• Build strong internal partnerships across GM’s field ecosystem
• Support product and feature launches to ensure aligned marketing and messaging
• Resolve dealer and customer satisfaction issues through appropriate channels
• Inspire belief in OnStar and GM’s connected ecosystem
• Conduct regular performance reviews, identify opportunities, and co‑create dealer action plans
• Bring a “Better Never Stops” mindset to everything you do.

District Manager – OnStar Fleet & Commercial

QA Engineer

• Execute APQP process with those Suppliers assigned to meet or exceed program work.
• Execute Program Reviews to program achievements and escalate issues appropriately.
• Ensure supply base adheres to GM standards and quality and manufacturing processes are enabled to identify out of standards conditions while preventing them to move to the next process or manufacturing site.
• React to out of standard conditions are work cross functionally to resolve known issues in a timely manner.
• Performs other related duties as assigned.

Supplier Quality Engineer

Product Manager

• Set and evolve the vision, strategy, and roadmap for GM’s Unified Entitlement & Fulfillment Platform
• Lead roadmap execution and prioritize the platform backlog
• Own data quality, KPIs, and observability for entitlement and fulfillment flows
• Act as the primary cross‑functional leader and storyteller for the platform

Group Product Manager – Unified Entitlement & Fulfillment

Data Analyst

• Lead analytics projects with key stakeholders in information technology, purchasing, operations, finance, sales and marketing, and external service providers
• Lead Finished Vehicle forecasting process
• Build and automate analytics tools to assist in key goals
• Utilize predictive analytics to assist in future network planning
• Support the business with ad hoc data mining

Logistics Manager – Finished Vehicle Data Analytics

Engineer

• Own fusion performance for assigned vehicle platforms from initiation through launch and field performance support.
• Lead vehicle and simulation testing to characterize and develop fusion performance, including test design, data collection, test execution, and results analysis for a wide range of environments, traffic scenarios, and edge cases.
• Develop and optimize fusion-related parameters utilizing big data, ensuring robust operation across vehicle lines and hardware variants, and delivering production-ready calibrations to programs on time.
• Serve as the single-point technical contact for fusion performance root cause and issue resolution, including correlation between sensor-level behavior and fused object/scene outputs.
• Collaborate with sensor performance engineers (radar, camera, lidar, etc.) to align sensor requirements and capabilities with fusion algorithm needs and feature performance targets.
• Use simulation and data-driven methods (e.g., SIL/HIL, scenario-based testing, replay of recorded data) to evaluate, regress, and improve fusion algorithms and calibrations, complementing vehicle testing.
• Analyze complex data sets from on-road vehicles, proving ground tests, and virtual environments to identify performance gaps, sensitivity to environmental factors, and opportunities for algorithm or calibration improvements.
• Support cross-functional technical discussions and reviews with ADAS software, perception, planning, systems, program teams, safety, and validation to drive alignment on fusion performance decisions and trade-offs.
• Support validation and verification activities for fusion-impacted features, such as Adaptive Cruise Control and Automatic Emergency Braking.
• Document and communicate results, lessons learned, and issues; contribute to standardized methods, tools, and metrics for fusion performance within the broader ADAS organization and program milestones.

ADAS Fusion Performance Engineer

Financial Planning and Analysis

• Support Sales and Marketing team by assisting the organization with high quality and timely responses to inquiries for financial information.
• Consolidate budget/forecasting and closing results, preparing variance explanations (Profit) promoting initiatives to improve accuracy.
• Support business cases financials with reliable conclusions that management can use to implement more effective operational strategies.
• Proactively identify risks and opportunities for the business.
• Propose improvements in periodic analysis, optimize files and procedures.
• Maintain outstanding relationships with business partners anticipating their needs (proactive vs. reactive).
• Responsible for pricing routine preparing build-ups analysis for Manufacturer Suggested Retail Price, Price with exemptions (person with a disability and taxi) and government bidding.
• Register price assumptions at Mainframe system.
• Preparer and report Price Plan.

Finance Price Specialist

Data Scientist

• Drive the design, delivery, and adoption of advanced analytics and machine learning solutions.
• Define and evolve the data science roadmap for GM Motorsports.
• Architect end-to-end ML and analytical solutions.
• Lead high-visibility projects from problem framing through delivery.
• Partner with race engineers and program managers to identify AI/ML opportunities.
• Provide technical mentorship and code/analysis review for junior and senior data scientists.
• Communicate complex analytical concepts to non-technical stakeholders.
• Champion data quality, governance, and responsible AI practices.

Staff Data Scientist – Motorsports

Controller

• Do you want to investigate and solve software and control system problems encountered in our products; and do you enjoy helping people encountering issues and enabling them to make progress?
• In this role as a Controller Integration Engineer, you will do that by troubleshooting HIL, vehicle system bench and vehicle integration issues using system engineering knowledge to isolate causes, establishing root cause and potential solutions.
• Troubleshoot engine, transmission, hybrid, electrification, chassis, and intelligent brake control system issues through all the different life cycle stages on the full range of GM vehicles.
• Work closely with our internal development teams including manufacturing, controls development, software, calibration and testing activities, as well as other cross functional teams.

Controller Integration Engineer – VMEC

• Develop & Sustain Power BI dashboards
• Develop and sustain AI agents
• Identify newer technologies team should be using and cross train others
• Develop and automate manual processes
• Collaborate cross-functionally to source and prioritize data effectively
• Utilize tools such as Partsmart (PIM), Erapa, ARC, Databricks, Knime, Power BI, Access databases, and SQL
• Develop & maintain Photography Strategy (physical and AI rendering)
• Work cross functionally with PDC & Warehouse leadership and UAW members
• Understanding of OE and Aftermarket content including ACES & PIES
• Collaborate and manage competing priorities with the Product Information Management (PIM) team, National Accounts, eCommerce, GM Parts Connect and other teams.
• Be able to lead and drive conversations
• Drive solutions to fill data gaps and perform data audits
• Ability to interpret data and tell a story about the data to leadership
• Produce visuals that help tell the story
• Develop and implement new processes, provide feedback, and work with others to ensure continuous improvement

Part Content & Analytics Lead

Full-stack Engineer

• Own critical pieces of the compute platform, from kernel configuration and BSP integration to device drivers and system services for GM’s digital cockpit and vehicle compute systems.
• Build and maintain Yocto-based embedded Linux distributions and associated build pipelines that ship on high-volume vehicle programs.
• Drive system performance, optimization, and complex debugging, using low-level tools (e.g., perf, ftrace, gdb, tracing/profiling) to diagnose issues across software and hardware boundaries.
• Work deeply in Linux/UNIX environments — living at the command line, automating workflows with shell and Python, and refining build systems (Make and related tools) to keep the platform reliable and reproducible.
• Partner with Qualcomm and other silicon vendors to bring up new SoCs, integrate vendor deliverables, and tune platform features for GM-specific use cases.
• Provide technical leadership within the team, mentoring others and helping drive engineering standards and best practices across the stack.

Staff Software Engineer – Compute Systems Software, Embedded OS

Hardware Engineer

• Define end-to-end GNSS hardware and system requirements for connectivity and compute modules, including RF front-end, baseband, timing, and antenna interfaces.
• Translate product and vehicle-level requirements into clear, testable engineering specifications for GNSS performance.
• Own GNSS-related sections of hardware requirement documents, design guidelines, and interface specifications.
• Collaborate with Product Management and Systems Engineering to understand use cases, feature roadmaps, and vehicle integration constraints.
• Partner with Vehicle Integration and Validation teams to align GNSS performance metrics and test plans with vehicle-level targets.
• Lead and participate in design and technical reviews focused on GNSS architecture, hardware design, and validation strategy.
• Work with GNSS chipset/module and RF component suppliers to evaluate and select GNSS solutions.
• Influence supplier technology roadmaps to align with our long-term product strategy.
• Collaborate with Purchasing to evaluate and score technical proposals and RFQs.
• Develop schematics for GNSS signal chains, including RF front-end, matching networks, filtering, and protection circuitry.
• Review and approve PCB layouts for GNSS sections, focusing on RF best practices.

Staff Hardware Engineer – GNSS Connectivity

Designer

• Design dealer-facing digital products including inventory management, sales tools, reporting dashboards, and customer-facing workflows for onboarding.
• Collaborate closely with Research, Product, Engineering, and Design Systems teams to ensure your designs are feasible, scalable, and aligned to design systems.
• Create high-fidelity prototypes, wireframes, and interaction models.
• Advocate for consistency, accessibility, and usability across all dealer tools and customer interfaces.

Senior Designer – HID Onboarding, Integrations

• Lead GM’s enterprise capabilities for threat intelligence, security investigations, security monitoring, and coordinated response to critical security incidents.
• Identify, assess, and mitigate risks to employees, assets, operations, and reputation through intelligence‑led analysis, disciplined investigative practices, and effective cross‑functional response coordination during high‑impact events.
• Serve as a trusted advisor to Global Security functional teams and senior leadership, providing timely insights and risk‑based decision support during emerging threats and critical situations.
• Provide strategic oversight of the GSOC, delivering a resilient 24/7 global capability for threat monitoring, incident escalation, and coordinated response.
• Promote a culture of disciplined execution, sound judgment, collaboration, and calm decision‑making under pressure.
• Oversee GSOC performance metrics, staffing models, training, and use of enabling technology to drive reliability and resilience.
• Lead global threat intelligence and risk assessment capabilities supporting travel security, site risk management, executive protection, and business operations.

Senior Manager, Intelligence, Investigations and Incident Management

Machine Learning Engineer

• Build high‑impact labeling experiences
• Design, implement, and test scalable, high‑performance user experiences and services using modern full‑stack and/or frontend technologies.
• Develop automation and tooling that give ML engineers deep insight into labeling workflows and data quality (e.g., efficiency dashboards, auto‑QA, autolabel review tools), reducing iteration time from idea to trained model.
• Collaborate with ML engineers to design and integrate ML‑driven data annotation (pre‑labeling, autolabeling, active learning loops), helping us move from human‑only to machine‑led labeling at scale.
• Use and advocate for modern AI‑powered development workflows (code assistants, automated documentation, test generation, etc.) to increase velocity while maintaining quality.
• Take ownership of technical projects from problem framing through design, implementation, and rollout.
• Drive code reviews, design discussions, and technical decisions.
• Work with partner teams (ML, Ops, Product, Data Science, other platform teams) to translate abstract requirements into concrete workflows, APIs, and UIs that hit quality, cost, and latency goals.

Senior AI/ML Engineer

Data Engineer

• Own the end-to-end design, development, and operation of scalable data engineering pipelines and backend services using Java, Quarkus , Spring Boot ensuring reliability, observability, and maintainability
• Lead the design and implementation of cron-based and event-driven orchestration services that retrieve and process data from multiple enterprise systems via REST APIs and messaging platforms
• Architect and implement real-time data processing solutions using Kafka and Azure Event Hub, including schema design, consumer group strategy, and resiliency patterns
• Design and optimize relational data models and database solutions using PostgreSQL and other relational data stores, including indexing strategies, query optimization, and performance tuning at scale
• Drive the deployment, scaling, and lifecycle management of services on Azure Kubernetes Service (AKS), including workload identity, networking, and security configuration
• Define and implement CI/CD pipelines using GitHub Actions/Workflows, and manage automated, GitOps-based deployments using ArgoCD across multiple environments
• Lead infrastructure automation using Terraform, establishing reusable modules, environment standards, and best practices for cloud resource provisioning and governance, including Datadog monitor creation and management
• Design and implement end-to-end observability using Prometheus, Datadog, and related tooling, including metrics, logs, traces, dashboards, and alerting with clear SLOs/SLIs
• Build and maintain data processing workflows using Databricks and distributed data frameworks, including batch and streaming jobs, job orchestration, and cost-optimized compute
• Collaborate closely with product, architecture, and cross-functional engineering teams to refine requirements, define technical roadmaps, and translate business outcomes into robust technical designs
• Drive performance, reliability, and scalability improvements across data and service layers, including load testing, capacity planning, and performance benchmarking
• Troubleshoot complex production issues, perform root cause analysis, and implement durable fixes and resiliency patterns.
• Champion engineering best practices (code reviews, testing strategy, documentation, security, and monitoring) and help evolve team standards, patterns, and reference architectures
• Mentor and coach engineers on the team, providing technical guidance, pairing, and feedback to elevate overall engineering quality and delivery.