General Motors
Staff AI Developer and Machine Learning Engineer
General Motors, Milford, Connecticut, United States, 06466
Overview
Staff AI Developer and Machine Learning Engineer at General Motors. Hybrid role; report to Milford, Michigan three times per week. Responsibilities
Prototype and productionize scalable AI systems, focusing 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 RAG systems, fine-tuning vs. zero/few-shot learning, and implement feedback loops for continuous improvement. Advance multi-agent AI systems, context-aware simulation orchestration, and generative design techniques. Develop custom feature extraction methods for predictive modeling 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 results. 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 evaluation, monitoring, and retraining mechanisms. Cross-Functional Collaboration
Serve as a technical liaison between simulation teams, software development, platform/cloud architects, hardware 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 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. Qualifications
Bachelor’s in Computer Science, Engineering, Mathematics, or related field (specifically NLP, simulation AI, or reinforcement learning). 7+ years of experience building and deploying advanced ML/DL systems in production. Demonstrated expertise with LLMs, transformer architectures, AI agents, or simulation-integrated models. Strong experience in Python, ML frameworks (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). 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 ability to collaborate cross-functionally. Competitive Advantage (Preferred Qualifications)
Master’s or PhD in a related field (NLP, simulation AI, reinforcement learning). 7+ years of production ML/DL experience. 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 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 to identify novel AI applications in engineering workflows. Strategic ownership to drive initiatives from concept to integration. Cross-domain fluency connecting simulation, embedded systems, and data science. Commitment to mentorship and scaling expertise across the team. Benefits
GM offers a variety of health and wellbeing benefits, including medical, dental, vision, HSA/FSAs, retirement plan, life insurance, vacation and holidays, tuition assistance, employee assistance program, and vehicle discounts. Company Vehicle
Eligible to participate in a company vehicle evaluation program after motor vehicle report review; participants must purchase/lease a qualifying GM vehicle every four years unless exceptions apply. This job may be eligible for relocation benefits. About GM
Our vision is Zero Crashes, Zero Emissions and Zero Congestion; we lead the change to make the world better, safer, and more equitable for all. Equal Opportunity
General Motors is an equal opportunity employer. All employment decisions are made without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, veteran status, or other protected statuses, in accordance with laws. Applicants may be required to complete role-related assessments or pre-employment screenings. To learn more, visit How we Hire. Accommodations
GM offers accommodations for job seekers with disabilities. If you need an accommodation, please email or call us with details and the job title and requisition number.
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Staff AI Developer and Machine Learning Engineer at General Motors. Hybrid role; report to Milford, Michigan three times per week. Responsibilities
Prototype and productionize scalable AI systems, focusing 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 RAG systems, fine-tuning vs. zero/few-shot learning, and implement feedback loops for continuous improvement. Advance multi-agent AI systems, context-aware simulation orchestration, and generative design techniques. Develop custom feature extraction methods for predictive modeling 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 results. 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 evaluation, monitoring, and retraining mechanisms. Cross-Functional Collaboration
Serve as a technical liaison between simulation teams, software development, platform/cloud architects, hardware 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 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. Qualifications
Bachelor’s in Computer Science, Engineering, Mathematics, or related field (specifically NLP, simulation AI, or reinforcement learning). 7+ years of experience building and deploying advanced ML/DL systems in production. Demonstrated expertise with LLMs, transformer architectures, AI agents, or simulation-integrated models. Strong experience in Python, ML frameworks (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). 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 ability to collaborate cross-functionally. Competitive Advantage (Preferred Qualifications)
Master’s or PhD in a related field (NLP, simulation AI, reinforcement learning). 7+ years of production ML/DL experience. 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 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 to identify novel AI applications in engineering workflows. Strategic ownership to drive initiatives from concept to integration. Cross-domain fluency connecting simulation, embedded systems, and data science. Commitment to mentorship and scaling expertise across the team. Benefits
GM offers a variety of health and wellbeing benefits, including medical, dental, vision, HSA/FSAs, retirement plan, life insurance, vacation and holidays, tuition assistance, employee assistance program, and vehicle discounts. Company Vehicle
Eligible to participate in a company vehicle evaluation program after motor vehicle report review; participants must purchase/lease a qualifying GM vehicle every four years unless exceptions apply. This job may be eligible for relocation benefits. About GM
Our vision is Zero Crashes, Zero Emissions and Zero Congestion; we lead the change to make the world better, safer, and more equitable for all. Equal Opportunity
General Motors is an equal opportunity employer. All employment decisions are made without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, veteran status, or other protected statuses, in accordance with laws. Applicants may be required to complete role-related assessments or pre-employment screenings. To learn more, visit How we Hire. Accommodations
GM offers accommodations for job seekers with disabilities. If you need an accommodation, please email or call us with details and the job title and requisition number.
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