Staff AI/ML Software Engineer, Model Distillation & Fine-Tuning
General Motors1 day ago
Base Salary
$189k - $291k/yr
Responsibilities
- Design and build knowledge-distillation pipelines that transfer reasoning, vision, and language capabilities from foundation models into compact edge-deployed architectures.
- Apply and scale parameter-efficient fine-tuning techniques such as LoRA and QLoRA for cabin interaction and conversational AI use cases.
- Build and own the reinforcement-learning improvement loop, including human-in-the-loop alignment with RLHF and DPO.
- Curate, evaluate, and synthetically generate datasets for passenger-intent interpretation and complex in-vehicle visual cues.
- Implement quantization-aware training and related techniques to preserve accuracy when models are compressed for hardware deployment.
- Establish evaluation frameworks and benchmarks covering hallucination rates, domain accuracy, and safety constraints.
- Own the base-model strategy and determine which foundation architectures to adopt.
- Set architectural direction for ML optimization pipelines and connect foundation-model research with vehicle-edge deployment.
Requirements
- Bachelor’s degree in Computer Science, Machine Learning, Data Science, Mathematics, or equivalent practical experience.
- At least 8 years of software engineering or applied ML research experience, including setting technical direction, making architectural decisions for ML systems, and influencing 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 from Mountain View, CA or Seattle, WA, with at least three days per week in the office.
- Preferred: Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
- Preferred: experience shipping a quantized model to a hardware target and resolving accuracy regressions.
- Preferred: familiarity with Hugging Face, DeepSpeed, Ray, or Megatron and experience managing large-scale dataset pipelines.
- Preferred: domain experience in conversational AI, human-computer interaction, smart spaces, or multimodal consumer products.
- Preferred: open-source contributions or published research involving foundation-model tuning, compression, distillation, or efficient AI.
- Preferred: ability to communicate AI training concepts and architectural trade-offs to cross-functional teams.
Benefits
- Hybrid work arrangement in Mountain View, CA or Seattle, WA, with a minimum of three office days per week.
- Eligibility for a company vehicle evaluation program after successful motor vehicle report review, subject to program requirements.
- Potential eligibility for relocation benefits.
- Employee benefits and total-rewards resources are available from day one.
- Non-discrimination, inclusion, and reasonable workplace accommodation support are provided.
Tech Stack
Categories
About General Motors
General Motors designs, manufactures, and sells cars, trucks, and electric vehicles for consumers and commercial fleets under brands including Chevrolet, GMC, Cadillac, and Buick. A public company on the NYSE headquartered in Detroit and founded in 1908, it operates globally and is developing EVs on its Ultium battery platform. Revenue comes from vehicle and parts sales, connected services such as OnStar, and financing through GM Financial.