ML Engineer with 7+ years of industry experience in building robust, large-scale AI solutions using Python, SQL, TensorFlow, and PyTorch. Expertise in developing and deploying traditional ML and LLM models across cloud platforms like GCP and AWS.

• Machine Learning Engineer at CVS Health (Dec 2023 - Present)
• Machine Learning Engineer at Schneider Electric (Jul 2022 - Dec 2022)
• Senior Machine Learning Engineer at Honeywell (Oct 2019 - Jul 2021)
• Machine Learning Engineer at Honeywell (Jul 2017 - Sep 2019)
• Machine Learning Engineer at Centre of Artificial and Machine Intelligence (Jan 2016 - Jun 2017)

Developed an end-to-end RAG-based LLM system for parsing PBM medical contracts and generating accurate contextual responses for contract queries, reducing review time by 65% and improving compliance accuracy by 40% for healthcare stakeholders.

Engineered a standardized ML framework with modular KubeFlow components for complete model lifecycle, reducing deployment time by 70% and increasing team collaboration by 45%.

Architectured an AI Platform to aggregate and centralize 700+ ML models, resulting in faster large-scale production deployments.

Architectured a Deep Reinforcement Learning-based Database Recommendation System, spiking click-through rates by 20% and enhancing performance using Actor-Critic model with 10% jump in user engagement.

• NeurIPS Workshop, HyperCube-based Accelerated DBSCAN (Dec 2019)
• IEEE Conference (ICCCSP), Face Detection and Tagging using Deep Learning (Feb 2018)

• Master of Science - Computer Science, Northeastern University
• Bachelor of Technology - Computer Science, Manipal University

• Email: mehtajineshs@gmail.com
• GitHub: mehtajinesh
• LinkedIn: mehtajineshs

• Advanced LLM Fine-tuning Techniques
• Reinforcement Learning from Human Feedback (RLHF)
• Vector Database Optimization for RAG Systems

⭐️ From mehtajinesh