Remote: Yes (preferred)

Willing to relocate: No

Technologies: GenAI: LangGraph, AutoGen, Google ADK, RAG systems Backend/Data: Python, FastAPI, PostgreSQL, DuckDB Cloud: Azure, Databricks, Docker, Kubernetes

Résumé: https://manish-m.com/resume.pdf

Email: workdesk manish [at] gmail com

I build and ship production GenAI systems in pharma (R&D + TechOps), leading a team of 4. My work spans data pipelines, backend systems, and cloud infrastructure to deliver production-ready AI applications.

Recent work:

Report generation framework (unstructured + structured data → compliant reports) Processes PDFs, documents, and structured datasets to generate consistent, audit-ready reports GxP-compliant intelligent QMS collaborator (~40% faster QA workflows)

Most of my work is in regulated environments, so I focus on traceability, observability, and building reliable AI systems.

Looking for- Roles: AI Engineer / ML Engineer / Data Scientist Commitment: Full-time / Part-time (freelance, IC)

Remote: Yes (preferred)

Willing to relocate: No

Technologies: ML/DL/AI/LLMs: PyTorch, GNNs, LangChain, GraphRAG, Ollama, vLLM, MLFlow; Backend: Python, PostgreSQL, DuckDB, FastAPI; Cloud Infrastructure: Docker, Kubernetes, Azure (AI Foundry, Search, Container Apps),

Résumé/CV: https://manish-m.com | https://linkedin.com/in/manish-mishra-908329192

Email: workdesk manish [at] gmail com

Full Stack Data Scientist & AI Engineer with 3+ years building production AI solutions for drug discovery. My job at https://aganitha.ai requires rapid prototyping from latest GenAI research to production-ready ML pipelines for high-throughput data processing.

I have recently worked on:

- AskLLM: Plug-and-play framework for React applications that extracts structured context from UI widgets, enabling intelligent user assistance beyond traditional UX

- Company-wide MCP (Model Context Protocol) framework consolidating all tools and pipelines (comp bio, comp chem), with enhanced job management capabilities for long-running processes

- Event-driven automated ETL pipelines in Azure ecosystem for continuous document evaluation using Logic Apps, Databricks, and Genie AI/BI

Looking for full time Data Scientist/GenAI Engineer roles.