Jasleen Singh — AI Researcher
Building resilient, production-grade AI systems for the real world I work on making GenAI and LLMOps actually production-ready, reliable, explainable, and cost-efficient. What I build: • Agentic workflows with LangGraph that can run for days without intervention. • RAG-optimized document processors (LangChain + Hugging Face + ChromaDB), 30% faster lookup, containerized on GCP. • GenAI-powered browser automation (LangGraph + Playwright) with stateful Redis persistence — 40% faster, enterprise-grade. • Observability and monitoring pipelines that save 35% GPU cost (and countless debugging hours). How I work: I treat MCP tools like my personal Swiss Army knife... chaining agents, testing evals, and deciding daily between prompt engineering and transformer-level fine-tuning. What I’ve learned: • Most GenAI failures are orchestration issues, not model issues. • Monitoring beats magic; boring infra scales better than clever prototypes. • Reliability is the real frontier of LLM engineering. If you’re shipping real AI products or have production war stories, let’s connect
Stackforce AI infers this person is a skilled AI/ML Engineer specializing in production-ready generative AI solutions.
Location: Pune, Maharashtra, India
Experience: 8 mos
Skills
- Machine Learning
- Generative Ai Tools
Career Highlights
- Expert in building reliable AI systems.
- Proven track record in optimizing AI workflows.
- Strong focus on cost-efficient AI solutions.
Work Experience
RIA Advisory
AI ML Engineer (8 mos)
AI ML INTERN (5 mos)
Education
Bachelor of Technology - BTech at Medicaps University
