Open to opportunities

Sharven Rane

@sharvenrane

Medical imaging and computer vision AI engineer delivering regulated, production-ready models from validation to deployment.

United States

Message

What I'm looking for

I’m looking to build and validate clinically accountable computer-vision and medical-imaging ML in regulated settings, partnering cross-functionally to deliver model risk management, explainability, and production MLOps with strong governance.

I build medical imaging AI with the discipline required for clinical and safety-critical settings, with regulated AI experience aligned to FDA 21 CFR Part 11 and GxP. I’ve trained and validated deep learning models across 250K+ radiographic studies and 50+ conditions, owning the lifecycle from training through validation, governance, and production deployment.

I combine hands-on computer vision development with model validation, model risk, and explainability to earn stakeholder trust. In production roles, I’ve modernized and scaled training pipelines, delivered segmentation and detection systems, and integrated monitoring and validation artifacts (e.g., data drift checks, sensitivity/specificity reporting) into deployments to reduce latency and cloud costs.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

Vetology

Oct 2024 - Present (1 year 8 months)

Modernized Vetology’s AI infrastructure by migrating 150+ TensorFlow models and converting 30+ YOLO object-detection models to PyTorch for scalable production deployment. Built a UNet++/DeepLabV3+ segmentation pipeline (97.5% Dice) and deployed 200+ clinical-grade models using validation artifacts (drift checks, sensitivity/specificity) that reduced latency 30% and cloud costs 20% across 250K+ rad

PyTorch TensorFlow YOLO UNet++DeepLabV3+Onnx MLFlow Model Governance CI CD

Machine Learning Engineer

Get Hire Technologies

Dec 2023 - Oct 2024 (10 months)

Built ETL and feature-engineering workflows to ingest life-sciences instrument logs and metadata, enabling classification/regression/time-series models (85–90% accuracy) for instrument failure and experiment-success forecasting. Implemented model monitoring, data drift detection, and regulated-compliance workflows (GxP, FDA 21 CFR Part 11) and deployed ML models into Django analytics dashboards, i

Python SQL Pandas Airflow AWS S3 Model Monitoring Model Data Drift Detection Time Series Modeling

Data Engineer

Vighnaharta

Apr 2021 - May 2022 (1 year 1 month)

Automated IoT intrusion-system data collection and telemetry parsing, analyzing sensor logs and failure patterns to improve reliability and support R&D insights. Built device provisioning and configuration-validation utilities that reduced setup time 25%, supported field deployment/monitoring of 150+ security devices, and reduced recurring errors by 15%.

Python IoT Telemetry Parsing Automated Provisioning

Education

Degrees, certifications, and relevant coursework

Stevens Institute of Technology

Master of Science, Data Science

2022 - 2023

Earned a Master of Science in Data Science with an accelerated track, completing the program in about 1.5 years. Achieved top-of-class distinction and academic recognition in applied data science coursework.

Savitribai Phule Pune University (SPPU)

Bachelor of Engineering, Computer Science Engineering

2018 - 2022

Completed a Bachelor of Engineering with a major in Computer Science Engineering and honors in Data Science. Received academic awards and was part of the first graduating batch to receive Honors in Data Science.