Staff AI Developer and Machine Learning Engineer

Job 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. Were 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.

Youll 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. Were 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 Youll 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 GMs 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 Job Description

Your Skills & Abilities (Required Qualifications):

• Bachelors 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):

• Masters 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.

Benefits Overview

From day one were looking out for your well-beingat work and at homeso you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards Resources.

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.

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