Senior 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
- 10+ 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.
- Expert in Python and R.
- Experience with LLM platforms such as OpenAI, Anthropic, or Gemini.
- Strong communication and client-facing skills working with Clients.
- Linkedin Profile with Picture.
- ID might be requested for technical interviews and tests.
Nice To Haves
- Experience with Amazon Neptune or other graph databases a must.
- 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
- Experience delivering end-to-end ML/AI solutions from problem framing through deployment and monitoring from a consultant perspective.
- Design scalable AI/ML architectures using AWS, Azure, 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
