Skills
A technical stack shaped by real delivery work, not keyword stuffing.
The tools and patterns I rely on most across applied ML, systems engineering, cloud delivery, and research-heavy product work.
Applied ML & Generative AI
Production modeling, retrieval, and LLM systems with an emphasis on evaluation, accuracy, and shipping.
Python
PyTorch
TensorFlow
Transformers
GraphRAG
Multi-Agent Systems
FastAPI
Whisper
Quantum Computing
Algorithms and benchmark-driven experimentation where correctness, not hype, determines what is useful.
Qiskit
QAOA
Grover's Algorithm
Quantum RAM
Error Correction
Benchmarking
Cloud, Data & MLOps
The platform and data layer that turns prototypes into dependable, monitored services.
Databricks
PySpark
Snowflake
Docker
Kubernetes
GCP / Azure / AWS
CI / CD
Redis
Systems & Product Engineering
Typed frontends, backend architecture, and security-conscious delivery for real product workflows.
Next.js
TypeScript
Rust
C# / .NET
Neo4j + ChromaDB
OAuth / JWT / RBAC
gRPC / REST APIs
Event-Driven Systems