Shekhar Tanwar

Machine Learning Engineer @ United Health Care
10+ Years Of Experience in Machine Learning and Natural Language Processing
United States of America
Speaks English and Hindi
Active this week

Services

$200 / month

Best suited for mentees who want to switch roles to Data Scientist or Machine Learning Engineer.

2 calls per month (34min/call)

Unlimited Q&A via chat

Expect responses in 24 hours or less

Hands-on support

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About

Hi, I’m Shekhar.

I am a Senior Machine Learning Engineer with 10+ years of experience designing and deploying large-scale NLP, Search, and Generative AI systems in production. My work spans end-to-end ownership of Query Understanding, Representation Learning, Retrieval, and LLM/SLM evaluation pipelines that serve millions of requests daily at sub-200 ms latency.

Across companies like DoorDash, UnitedHealth Group, and Highmark, I have led initiatives that improved retrieval recall from ~79% to 95%, reduced claim and case resolution times by up to 85%, and built robust LLM evaluation systems (“LLM Judges”) that assess models across 15+ qualitative, compliance, and safety dimensions. I specialize in fine-tuning embedding models, SLMs, and LLMs (LoRA, PEFT, DDP), architecting hybrid search systems (BM25 + vectors), and operationalizing agentic workflows for data annotation, evaluation, and RAG.

Who I mentor and how I help:

I work best with engineers and researchers who want to move beyond theory and build real, production-grade ML systems. Typical mentees include:
• ML Engineers aiming to break into Search, Retrieval, or Relevance teams
• Engineers transitioning into Generative AI, RAG, or Agentic AI roles

My mentoring style is highly applied and system-oriented. Together, we can:
• Design and fine-tune embedding models and small language models for real-world retrieval and routing tasks
• Build end-to-end RAG systems with proper evaluation, monitoring, and cost controls
• Develop LLM evaluation frameworks (LLM-as-Judge, error taxonomies, offline + online metrics)
• Strengthen ML system design thinking, from data pipelines to inference optimization and deployment

You can expect concrete guidance, architecture reviews, hands-on debugging, and honest feedback grounded in production experience.

If you are serious about building scalable NLP and Generative AI systems and want mentorship that emphasizes depth, rigor, and real-world impact I’d be happy to work with you. Book a session, share your goals, and we’ll create a focused plan to help you grow faster and with confidence.