Agentic AI / Machine Learning Consultant
About The Position
Vertical Relevance is seeking an Agentic AI/ Machine Learning Consultant to join our team. In this role, you will be responsible for the end-to-end design, development, and deployment of advanced ML/AI solutions. You’ll work closely with clients to deliver impactful outcomes, leveraging Cloud services and cutting-edge technologies in the NY Metro Area. As an Agentic AI/Machine Learning Consultant, you will collaborate with cross-functional teams to implement technical solutions that solve complex business challenges. This position requires strong technical expertise, excellent communication skills, and a passion for driving customer success. At Vertical Relevance, we believe in teamwork, automation, continuous learning, and ownership. If you’re ready to innovate and make a measurable impact, we’d love to hear from you!
Requirements
- Experience building and deploying ML/AI solutions in AWS, GCP, or Azure
- Strong expertise in RAG systems and retrieval optimization
- Experience with vector databases and hybrid search techniques
- Knowledge of knowledge graph design and entity resolution
- Proficiency in Python (R is a plus)
- Experience with LLM platforms such as OpenAI, Anthropic, or Gemini
- Strong communication and client-facing skills
Nice To Haves
- Experience with Amazon Neptune or other graph databases
- Familiarity with information retrieval metrics
- Experience with self-hosted embeddings
- Healthcare domain knowledge (payer/claims)
- Experience with agentic AI frameworks such as LangGraph or MCP
Responsibilities
- Deliver end-to-end ML/AI solutions from problem framing through deployment and monitoring
- Design scalable AI/ML architectures using AWS and GCP services
- Optimize RAG pipelines including chunking, embeddings, hybrid search, and re-ranking
- Develop retrieval evaluation frameworks (Recall@K, Precision@K, MRR, nDCG)
- Design and implement knowledge graphs and ontologies
- Build data ingestion pipelines for structured and unstructured data
- Deploy solutions using AWS tools such as SageMaker, Bedrock, Lambda, and OpenSearch
- Implement self-hosted embedding models in secure environments
- Ensure compliance with PHI/PII data security requirements
- Collaborate with cross-functional teams and act as a technical advisor
- Mentor team members and contribute to technical thought leadership
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
