[Remote] AI/ML Engineer at General Motors

United States

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Not SpecifiedCompensation

N/AExperience Level

N/AJob Type

Not SpecifiedVisa

N/AIndustries

Requirements

Bachelor's or higher degree in Computer Science or equivalent major or equivalent experience
5+ years professional software engineering or machine learning engineering experience
5+ years specialized experience in AI/ML infrastructure, e.g., enabling distributed training for scaling large ML models
Strong programming skills in Python, with proficiency in frameworks such as PyTorch (preferred)
Experience building autonomous agents using frameworks like CrewAI, Agno, LangChain Agents, Autogen
Experience integrating multiple data sources and orchestrating multi-step agent workflows
Familiarity with vector databases and search retrieval techniques
Experience with distributed computing, GPU computing, and cloud environments (AWS, GCP, Azure)
Demonstrated ability to lead projects that bridge marketing, data science, and technology to drive measurable outcomes
Ability to simplify complex data strategies into actionable marketing solutions and communicate technical concepts to non-technical stakeholders
Strong collaborative mindset and experience working with cross-functional teams including marketers, engineers, data scientists, and agency partners
Strong experience with Databricks for large-scale data engineering, model training, and serving in production environments
Proven ability to optimize ML workloads for performance and cost within Azure-based cloud architecture
5+ years of experience running AI/ML solutions in production, including monitoring, retraining, and drift detection
Deep familiarity with MLflow, ideally MLflow 3.0, including model tracking, versioning, and governance

Responsibilities

Design, build, and deploy autonomous AI agents using LLMs and agentic architecture frameworks
Manage memory, tools, goals, and execution environments
Build interfaces between agents, internal data systems, RAG pipelines, and cloud-based services
Collaborate with internal teams and stakeholders to rapidly prototype and iterate on novel agent capabilities
Demonstrate software engineering (SWE) skills, focusing on distributed backend development, batch data processing
Experiment and learn the latest AI development
Elevate system design, diagnostics, and operational excellence to higher standards
Collaborate with cross-functional teams to integrate new features and technologies into the platform
Monitor, retrain, and drift detection in AI/ML solutions
Optimize ML workloads for performance and cost within Azure-based cloud architecture

Skills

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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