Staff AI Developer and Machine Learning Engineer

Description
Work Arrangement:
Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Milford, Michigan three times per week, at minimum.
Why Join Us
General Motors is at the forefront of transforming transportation through software-driven innovation. We're driven by our bold vision of a future with Zero Crashes, Zero Emissions, and Zero Congestion. As we push forward into an era of vehicle intelligence and digital engineering, Artificial Intelligence and Data Science are a cornerstone of our strategy.
You'll be part of a team that is pioneering the integration of simulation, automation, AI agents, large language models (LLMs), and machine learning into critical systems for vehicle design, calibration, and performance. We're seeking a Staff AI Developer and Data Scientist to serve as a key technical expert, shaping the evolution of our tools and infrastructure while delivering scalable, intelligent solutions that drive real-world engineering impact.
The Role:
As a Staff AI Developer and Data Scientist, you will operate as a senior technical expert and strategic contributor within a growing AI/ML-focused engineering team. You will architect and deploy scalable AI/ML systems (e.g., LLMs, AI agents, retrieval-augmented generation (RAG), and hybrid AI-simulation models) that enable transformative use cases across simulation, calibration, and product development.
You will work cross-functionally with engineers, data scientists, simulation specialists, domain experts and platform teams to define and execute high-impact AI/ML initiatives. Your role will blend hands-on development, technical direction-setting, and mentorship, helping GM scale next-generation capabilities.
What You'll Do:

• Prototype, and productionize scalable AI systems, with an emphasis on LLMs, simulation-aware models, and hybrid AI pipelines.
• Lead AI/ML integration into core engineering tools and simulation frameworks, ensuring robustness, interpretability, and physical relevance of outputs.
• Evaluate and define the appropriate use of RAG systems, fine-tuning vs. zero/few-shot learning strategies, and feedback loops for continuous improvement.
• Drive forward-thinking initiatives involving multi-agent AI systems, context-aware simulation orchestration, or generative design techniques.
• Develop custom feature extraction methods for predictive modeling then used in optimizations.
• Apply statistical methods, anomaly detection, and clustering to uncover patterns.
• Work with large scale data sets and collaborate with subject matter experts to incorporate physical interpretations of insights
• Create interactive data visualizations to communicate and interpret
• Design and build ML models that may be used as surrogates in simulations
• Develop and operationalize full-stack AI pipelines using MLOps practices (e.g., Docker, Kubernetes, FastAPI, MLFlow, cloud-native services).
• Define strategies for large-scale data ingestion, embedding generation, retrieval tuning, and prompt optimization in production environments.
• Ensure scalability, reproducibility, and performance of deployed models through well-defined evaluation, monitoring, and retraining mechanisms.
• Use data analytics and signal processing to analyze simulation output data using techniques like wavelet transforms and motif discovery (or other)

Cross-Functional Collaboration

• Serve as a key technical liaison between simulation teams, software development, platform/cloud architects, HW teams and AI/ML research teams.
• Translate complex engineering needs into actionable AI/ML solutions, balancing innovation with stability and traceability.
• Help define and evolve the technical roadmap for AI/ML within GM's digital twin and simulation ecosystem.

Mentorship & Influence

• Mentor engineers and data scientists, enabling growth in areas such as model architecture, deployment practices, and responsible AI.
• Establish and champion engineering best practices, coding standards, and documentation norms for AI/ML systems across teams.
• Participate in technical reviews, external publications, or internal tech talks to scale knowledge and influence strategy.

Additional Description
Your Skills & Abilities (Required Qualifications):

• Bachelor's in Computer Science, Engineering, Mathematics, or related field (particularly in NLP, simulation AI, or reinforcement learning).
• 7+ years of experience building and deploying advanced machine learning or deep learning systems in production.
• Demonstrated expertise with LLMs, transformer architectures, AI agents, or simulation-integrated models.
• Strong experience in Python, major ML frameworks (e.g., PyTorch, TensorFlow, HuggingFace Transformers), SQL, and signal processing libraries (PyWavelets, Tsfresh).
• Experience with retrieval-augmented generation (RAG), prompt engineering, and embedding optimization.
• Knowledge of ML modeling and toolsets (e.g. Scikit-learn, XGBoost for classification/regression tasks)
• Experience with MLOps tools and deploying models via containerized microservices on cloud platforms.
• Proven ability to lead technical direction and deliver production-ready AI/ML systems at scale.
• Strong interpersonal and communication skills and a willingness to collaborate cross-functionally with different teams.

What Can Give You a Competitive Advantage (Preferred Qualifications):

• Master's or PhD in Computer Science, Engineering, Mathematics, or related field (particularly in NLP, simulation AI, or reinforcement learning).
• 7+ years of experience building and deploying advanced machine learning or deep learning systems in production.
• Experience in automotive or physical systems simulation domains.
• Familiarity with co-simulation frameworks, physical modeling (e.g., Simulink, Modelica), or system-level calibration workflows.
• Knowledge of optimization techniques such as PSO, GA, or MDO in the context of AI/simulation fusion.
• Contributions to open-source AI tools or published research in NLP, agents, or simulation-integrated AI.

What Will Give You a Competitive Edge:

• Visionary thinking: You identify and pursue novel AI applications in engineering workflows.
• Strategic ownership: You drive initiatives from concept to integration, influencing cross-org direction.
• Cross-domain fluency: You connect simulation, embedded systems, and data science to deliver tangible value.
• Commitment to mentorship: You uplift others and scale your expertise across the team.

Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies."
This job may be eligible for relocation benefits.
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Total Rewards | Benefits Overview
From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.
Non-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
Accommodations
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