AI ML Engineer at global networking leader, shaping ML strategy and building high - performance systems. Innovating with AI technology to enhance network management and develop flagship products.
About the role
- Lead AI/ML Engineer for developing scalable ML/LLM services and RAG pipelines at Vanguard. Collaborating with cross-functional teams and implementing responsible AI practices.
Responsibilities
- Architect, build, and deploy RAG pipelines, including chunking, embeddings, vector stores, retrieval, ranking, grounding, and evaluation
- Design and implement Graph RAG solutions leveraging knowledge graphs for multi‑hop reasoning and structured retrieval
- Build robust, scalable ML/LLM services using Python (and Java where applicable) with well‑designed APIs and microservices
- Develop data processing pipelines for ingestion, transformation, metadata extraction, and indexing
- Implement observability, monitoring, evaluation harnesses, automated testing, and CI/CD for GenAI services
- Optimize retrieval quality, response accuracy, latency, and cost across model + retrieval layers
- Apply responsible AI, security, and governance practices for LLM systems (e.g., content filtering, guardrails, model monitoring)
- Collaborate with product, data engineering, and cloud platform teams to translate business problems into robust AI solutions
- Produce clear documentation, design specs, and operational runbooks for all delivered components
Requirements
- 3+ years of experience as an ML Engineer, AI Engineer, or similar role
- Hands‑on experience building GenAI applications and RAG systems end‑to‑end
- Strong proficiency in Python for ML/LLM development
- Experience with vector databases (e.g., pgvector, Pinecone, Weaviate, FAISS) and embedding models
- Knowledge of LLM frameworks (LangChain, LlamaIndex, Transformers, etc.)
- Strong understanding of cloud environments (AWS/Azure) and containerized deployments
- Solid software engineering foundations — APIs, microservices, version control, testing, CI/CD
- Experience with data pipelines, ETL/ELT, and processing unstructured data
- Ability to evaluate retrieval quality, implement ranking strategies, and build evaluation datasets
- Excellent communication skills and ability to work in cross‑functional teams.
Benefits
- Health insurance
- Professional development opportunities
- Paid time off
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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