Research intern applying machine learning techniques to impactful projects in Seagate's Software and Applied AI Research team. Opportunity to work on AI solutions, predictive maintenance, and more.
About the role
- Lead Machine Learning Engineer focused on Generative AI and LLMs. Building prototypes and supporting project evaluations in a hybrid work environment.
Responsibilities
- Design and build GenAI and LLM-based prototypes and MLPs
- Develop chatbots, copilots, summarization, and automation workflows
- Implement and evaluate RAG, embeddings, and LLM techniques
- Build PoCs using modern ML frameworks and cloud-native tools
- Support experiment design, benchmarking, and model evaluation
- Collaborate with product, data, and engineering teams
- Contribute to architecture discussions and technical decisions
- Apply MLOps best practices and support documentation and demos
Requirements
- 6+ years in software engineering or ML/AI engineering
- 2+ years hands-on with GenAI, LLMs, or advanced ML platforms
- Python expertise and production ML system development
- Experience with PyTorch, TensorFlow, HuggingFace, LangChain
- Hands-on work with RAG pipelines, embeddings, prompt engineering, LLM fine-tuning
- Experience with AWS, Azure, or GCP deployments
- Experience with NoSQL, relational, and vector databases
- MLOps tools: MLflow, Docker, Kubernetes
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