General Motors' Marketing Applied Sciences (MAS) team is seeking an experienced expert in Gen AI and machine learning to design and build scalable, reliable, and high-performance AI/ML products to support key business initiatives, aiming to transform GM's data into actionable, personalized experiences for marketing.
Requirements
- 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.
- Deep understanding of LLM internals (prompting, tokenization, inference, function calling).
- Experience integrating multiple data sources and orchestrating multi-step agent workflows.
- Familiarity with vector databases and search retrieval techniques.
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.
Other
- This role is based remotely but if you live within a 50-mile radius of an office [Atlanta, Austin, Detroit, Warren, or Mountain View], you are expected to report to that office three times a week, at minimum.
- Bachelors or higher degree in Computer Science or equivalent major or equivalent experience.
- 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.
