Staff AI/ML Software Engineer, Model Distillation, Fine-Tuning

General Motors

Staff AI/ML Engineer adapting and distilling foundation models for General Motors’ in-vehicle multimodal AI. Building efficient, quantized models for driver intent, conversational context, and cabin vision.

Posted 9/9/2026full-timeMountain View • California, Washington • 🇺🇸 United StatesLead💰 $189,300 - $290,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing machine learning architectures, particularly in knowledge distillation and reinforcement learning. Proficient in fine-tuning large language models and implementing quantization techniques for edge deployment.

Highest-signal resume keywords

Deep Proficiency In PytorchKnowledge DistillationParameter-Efficient Fine-TuningQuantization-Aware TrainingArchitectural Decision-Making

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningSoftware EngineeringData ScienceModel OptimizationReinforcement LearningDataset ManagementQuantizationFine-TuningHuman-Computer InteractionConversational AI

Soft Skills

CommunicationTechnical Leadership

Tools & Technologies

Hugging FaceDeepSpeedRayMegatron

Certifications & Qualifications

Bachelor's Degree In Computer ScienceMaster's Degree In Artificial IntelligencePh.D. In Computer Science

Industry Keywords

Edge-Deployable ArchitecturesModel CompressionAI Training ConceptsMultimodal ModelsConsumer-Facing Products

Tech Stack

Tools & technologies

PyTorchRay

About the role

Key responsibilities & impact

Design and build knowledge distillation pipelines transferring reasoning, vision, and language capabilities into compact edge-deployable architectures
Apply and scale parameter-efficient fine-tuning techniques such as LoRA and QLoRA
Build and own the reinforcement learning flywheel using human-in-the-loop alignment with RLHF/DPO
Connect in-cabin data collection with continuous model improvement
Curate, evaluate, and synthetically generate datasets for passenger intent and complex in-vehicle visual cues
Implement Quantization-Aware Training and related techniques to prevent accuracy degradation during hardware compression
Establish evaluation frameworks and benchmarks measuring hallucination rates, domain accuracy, and safety constraints
Own the base model strategy and decide which foundation architectures to use
Set architectural direction for model optimization pipelines as an individual-contributor technical leader
Validate AI capabilities on representative vehicle hardware and chart practical paths to scale

Requirements

What you’ll need

Bachelor's degree in Computer Science, Machine Learning, Data Science, Mathematics, or equivalent practical experience
8+ years of software engineering or applied ML research experience
Experience setting technical direction, making architectural decisions on ML systems, and guiding other engineers
Deep proficiency in PyTorch
Hands-on experience fine-tuning large language models or vision-language models
Practical experience with at least two of knowledge distillation, parameter-efficient fine-tuning, pruning, or quantization
Based in or willing to work hybrid out of Mountain View, CA or Seattle, WA, reporting to the office at least three days per week
Master's degree or Ph.D. in Computer Science, Artificial Intelligence, or a related field (preferred)
Experience shipping a quantized model to a specific hardware target
Familiarity with Hugging Face, DeepSpeed, Ray, or Megatron
Experience managing dataset pipelines at scale
Domain experience in conversational AI, human-computer interaction, smart spaces, or deploying multimodal models in consumer-facing products
Open-source contributions or published research in model compression, distillation, or efficient AI
Ability to communicate complex AI training concepts and architectural trade-offs to cross-functional teams

Benefits

Comp & perks

Bonus potential through an incentive pay program based on company performance, job level, and individual performance
Company vehicle evaluation program, subject to successful motor vehicle report review
Potential eligibility for relocation benefits
Benefits supporting well-being at work and home
Reasonable accommodations for applicants with disabilities