Junesh Gautam
AI Systems Engineer | End‑to‑End Intelligent Delivery
Designing, orchestrating and shipping production AI – from rapid problem framing and data strategy to model engineering, evaluation automation, scalable deployment surfaces and continuous improvement loops. Relentless focus: measurable business impact & technical elegance.
0+ yrs
Engineering
0+
Deployments & Builds
0+
Data / ML Pipelines
0+
Certifications
AI Systems Architecture
Problem decomposition → feature substrate → model topology choice → evaluation harness → rollout with policy & guardrails.
- LLM + Retrieval
- Predictive
- Trust / Eval
Data & MLOps Pipelines
Automated ingestion → validation → feature fabric → experiment tracking → registry → multi‑target deployment & drift sensing.
- Batch + Stream
- CI/CD
- Observability
Digital + Physical Fusion
Unifying simulation, telemetry & control with adaptive models for resilient, closed‑loop decision layers across environments.
- Edge / IoT
- Sim → Real
- Optimization
Python
TensorFlow
Django
FastAPI
PostgreSQL
Redis
Docker
RAG
LLMs
EvalOps
Edge AI
MLOps