// technical stack
Skills & Expertise
3+ years of hands-on experience with production ML systems across the full stack — from raw data to edge deployment.
Skill Proficiency
Languages & Tools
Python95%
SQL85%
Bash / Shell75%
Git88%
Machine Learning & Deep Learning
XGBoost / Random Forest90%
CNN / LSTM88%
Transformers (BERT/GPT)82%
YOLO / UNet85%
MLOps & Infrastructure
Docker / Kubernetes80%
MLflow / W&B88%
Apache Airflow82%
DVC / Feast78%
CI/CD Pipelines75%
Cloud Platforms
AWS (S3 / SageMaker / EC2)80%
GCP Vision API72%
Computer Vision
OpenCV90%
MediaPipe85%
TensorRT78%
RTSP / Camera Feeds82%
NLP & Language
Text Classification85%
Summarization / QA78%
HuggingFace Transformers82%
spaCy / NLTK75%
Edge Computing
Raspberry Pi85%
Kafka / MQTT / IoT80%
Ubuntu / Linux82%
GPS / Haversine75%
Technology Tag Cloud
PythonSQLBashGitXGBoostRandom ForestCNNLSTMBERTGPTYOLOUNetDockerKubernetesMLflowW&BAirflowDVCFeastCI/CDFlaskStreamlitAWS S3SageMakerAWS EC2GCP VisionOpenCVMediaPipeTensorRTRTSPClassificationSummarizationHuggingFacespaCyRaspberry PiKafkaMQTTUbuntuGPS/Haversine
Skill Radar
Hover over dots to see proficiency levels
Python / SQL90%
Computer Vision87%
MLOps82%
NLP / LLM79%
Cloud (AWS/GCP)76%
Edge AI83%
Deep Learning86%
Data Engineering80%
🌱 Currently Learning
Rust for systems programming
For ultra-low latency edge inference engines
LangChain & LLM Agents
Building autonomous AI workflows for safety analysis
Apache Flink (streaming)
Real-time ML features at scale for fleet telemetry
LoRA / PEFT fine-tuning
Efficient LLM adaptation for domain-specific NLP