General Motors

Senior Machine Learning Engineer

United States

Not SpecifiedCompensation
Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
AutomotiveIndustries

Requirements

Candidates must possess a Bachelor's degree or higher in Computer Science or an equivalent major, or have equivalent experience. A minimum of 5 years of professional software engineering or machine learning engineering experience is required, along with 5+ years of specialized experience in AI/ML infrastructure, such as enabling distributed training for large ML models. Strong programming skills in Python, proficiency in frameworks like PyTorch, and experience building autonomous agents using frameworks such as CrewAI, Agno, LangChain Agents, or Autogen are essential. A deep understanding of LLM internals, experience integrating multiple data sources and orchestrating multi-step agent workflows, familiarity with vector databases and search retrieval techniques, and experience with distributed computing, GPU computing, and cloud environments (AWS, GCP, Azure) are also required. Demonstrated ability to lead projects bridging marketing, data science, and technology, the ability to simplify complex data strategies, and strong collaborative skills are necessary.

Responsibilities

The Senior Machine Learning Engineer will design and build scalable, reliable, and high-performance AI/ML products, collaborating with product managers, data engineers, and data scientists to develop state-of-the-art AI solutions. Specific duties include building and utilizing AI-Agent capabilities, performing multi-modality MLLM model evaluation, fine-tuning, deployment, and bulk inference. Responsibilities also involve evaluating and improving data quality, providing cost estimation and analysis, and supporting data pipeline orchestration on distributed backend systems. The role includes designing, building, and deploying autonomous AI agents, managing their memory, tools, goals, and execution environments, and building interfaces between agents, internal data systems, RAG pipelines, and cloud-based services. Collaborating with internal teams to rapidly prototype and iterate on novel agent capabilities, demonstrating software engineering skills in distributed backend development and batch data processing, experimenting with the latest AI developments, and elevating system design, diagnostics, and operational excellence are key duties. The engineer will also collaborate with cross-functional teams to integrate new features and technologies into the platform.

Skills

Gen AI
Machine Learning
AI/ML Products
LLMs
Agentic Architecture
RAG Pipelines
Data Quality
Data Pipeline Orchestration
Cloud Services
Multi-modality MLLM

General Motors

Designs, manufactures, and sells vehicles

About General Motors

General Motors designs, manufactures, and sells vehicles and vehicle parts, catering to individual consumers, businesses, and government entities. The company operates in both traditional internal combustion engine vehicles and the growing electric vehicle (EV) market, generating revenue through vehicle sales and financing services. GM stands out from competitors with its commitment to community service, sustainability, and diversity, as evidenced by a majority female Board of Directors. The company's goal is to balance traditional automotive manufacturing with technological advancements in electric and autonomous vehicles.

Detroit, MichiganHeadquarters
1908Year Founded
$486.7MTotal Funding
IPOCompany Stage
Automotive & Transportation, Financial ServicesIndustries
10,001+Employees

Benefits

Paid Vacation
Paid Sick Leave
Paid Holidays
Parental Leave
Health Insurance
Dental Insurance
Vision Insurance
Life Insurance
401(k) Company Match
401(k) Retirement Plan
Tuition Reimbursement
Student Loan Assistance
Flexible Work Hours
Discount on GM vehicles

Risks

Shutting down Cruise Robotaxi may affect investor confidence in GM's AV strategy.
Chevrolet Equinox EV recall could harm GM's safety reputation.
Leadership transition in design may disrupt continuity and brand identity.

Differentiation

GM's Dynamic Fuel Management system enhances fuel efficiency in traditional vehicles.
GM leads in board diversity with 55% women directors.
GM's pivot to personal autonomous vehicles aligns with consumer trends.

Upsides

Partnership with Nvidia boosts GM's autonomous vehicle technology capabilities.
Collaboration with ChargePoint expands EV charging infrastructure, enhancing consumer appeal.
Bryan Nesbitt's appointment as design head may bring innovation to GM's vehicle design.

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