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I'm Rutvik Gadhiya, an AI/Machine Learning Engineer with over 4 years of hands-on experience building and deploying NLP, deep learning, and end-to-end AI solutions across education, healthcare, transportation, and finance. I specialize in GPT-4, LLMs, RAG pipelines, and MLOps, delivering scalable real-time inference APIs and cloud-native deployments. I love turning data into impact by automating scoring pipelines for thousands of textual responses, optimizing model serving for high-throughput environments, and collaborating across teams to tighten feedback loops and reduce costs. My experience spans Django and MongoDB backend systems, FastAPI/Flask services, and containerized pipelines on AKS, with a proven track record of improving accuracy, reliability, and speed while maintaining strong security and maintainability.…I'm Rutvik Gadhiya, an AI/Machine Learning Engineer with over 4 years of hands-on experience building and deploying NLP, deep learning, and end-to-end AI solutions across education, healthcare, transportation, and finance. I specialize in GPT-4, LLMs, RAG pipelines, and MLOps, delivering scalable real-time inference APIs and cloud-native deployments. I love turning data into impact by automating scoring pipelines for thousands of textual responses, optimizing model serving for high-throughput environments, and collaborating across teams to tighten feedback loops and reduce costs. My experience spans Django and MongoDB backend systems, FastAPI/Flask services, and containerized pipelines on AKS, with a proven track record of improving accuracy, reliability, and speed while maintaining strong security and maintainability.

Rutvik Gadhiya

Data Scientist, AI Engineer, AI Developer, +2

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I'm Rutvik Gadhiya, an AI/Machine Learning Engineer with over 4 years of hands-on experience building and deploying NLP, deep learning, and end-to-end AI solutions across education, healthcare, transportation, and finance. I specialize in GPT-4, LLMs, RAG pipelines, and MLOps, delivering scalable real-time inference APIs and cloud-native deployments. I love turning data into impact by automating scoring pipelines for thousands of textual responses, optimizing model serving for high-throughput environments, and collaborating across teams to tighten feedback loops and reduce costs. My experience spans Django and MongoDB backend systems, FastAPI/Flask services, and containerized pipelines on AKS, with a proven track record of improving accuracy, reliability, and speed while maintaining strong security and maintainability.…I'm Rutvik Gadhiya, an AI/Machine Learning Engineer with over 4 years of hands-on experience building and deploying NLP, deep learning, and end-to-end AI solutions across education, healthcare, transportation, and finance. I specialize in GPT-4, LLMs, RAG pipelines, and MLOps, delivering scalable real-time inference APIs and cloud-native deployments. I love turning data into impact by automating scoring pipelines for thousands of textual responses, optimizing model serving for high-throughput environments, and collaborating across teams to tighten feedback loops and reduce costs. My experience spans Django and MongoDB backend systems, FastAPI/Flask services, and containerized pipelines on AKS, with a proven track record of improving accuracy, reliability, and speed while maintaining strong security and maintainability.

Available to hire

I’m Rutvik Gadhiya, an AI/Machine Learning Engineer with over 4 years of hands-on experience building and deploying NLP, deep learning, and end-to-end AI solutions across education, healthcare, transportation, and finance. I specialize in GPT-4, LLMs, RAG pipelines, and MLOps, delivering scalable real-time inference APIs and cloud-native deployments.

I love turning data into impact by automating scoring pipelines for thousands of textual responses, optimizing model serving for high-throughput environments, and collaborating across teams to tighten feedback loops and reduce costs. My experience spans Django and MongoDB backend systems, FastAPI/Flask services, and containerized pipelines on AKS, with a proven track record of improving accuracy, reliability, and speed while maintaining strong security and maintainability.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

AI/Machine Learning Engineer at Royal Monarch Solutions LLC

July 1, 2024 - Present

Led development of an internal AI-driven assessment platform by building NLP pipelines using Python, spaCy, and NLTK; automated scoring of 10,000+ textual responses daily and reduced manual processing by 60%. Engineered hybrid scoring algorithms combining BERT embeddings, TF-IDF vectors, and semantic similarity models; improved evaluation accuracy by 35% and reduced manual review effort by over 70%. Architected a scalable Django + MongoDB backend, integrating preprocessing engines, rubric alignment logic, and ML inference modules; increased system throughput by 2× and supported multi-team adoption. Built secure, real-time inference APIs using FastAPI and Flask, handling 50,000+ monthly API requests with sub-200ms latency. Containerized ML services with Docker on AKS, achieving 99.9% uptime and auto-scaling to 5× peak workloads. Implemented CI/CD pipelines with Jenkins, Prometheus, and Grafana, reducing release cycles by 55% and saving 40 hours per month.

Data Scientist at San Joaquin Council of Governments

January 1, 2024 - May 1, 2024

Conducted EDA on 209,897+ vehicle trips and 2M+ passenger trips; built data pipelines to merge, clean, normalize, and restructure multi-year datasets, evaluating ridership and route efficiency. Developed an interactive Flask-based Vanpool Fare Calculator and performed route-level analyses with Matplotlib, Tableau, and Excel, identifying peak corridors, under-used vans, and occupancy trends. Built regression forecasting models using scikit-learn to predict fuel costs, VMT growth, and commute patterns; delivered recommendations for dynamic scheduling, optimized routing, and hybrid/electric van integration.

Machine Learning Engineer at Cell Technology Inc

May 1, 2023 - December 1, 2023

Built computer vision models using PyTorch to detect cellular morphology changes in 6,500+ immunoassay images, improving QC accuracy by 12% and reducing false positives in ELISA development. Developed time-series deep learning pipelines (CNN, LSTM, RNN) on metabolic assay data from 4,200+ patient samples, enabling early detection of metabolic stress and improving prediction reliability by 15%. Created generative AI workflows with prompt engineering to simulate rare cell-marker expression scenarios, generating 20,000+ synthetic datasets and expanding assay design coverage by 18% for drug discovery. Managed ML lifecycle on AWS with MLflow and Kubeflow, tracking 60+ experiments to ensure reproducibility, versioning, and scalable deployments.

Machine Learning Engineer at Exelance IT

May 1, 2019 - June 1, 2022

Developed interactive dashboards and visualizations using Power BI, Amazon QuickSight, Plotly, and Seaborn for stakeholders, enabling actionable insights and improving data-driven decision efficiency across multiple projects. Implemented regression, classification, and XGBoost models, improving model accuracy by 25% and reducing data-driven decision latency. Built ETL pipelines and data preprocessing workflows using Pandas, NumPy, and SQL (MySQL, PostgreSQL), processing 2M+ records monthly and reducing data-cleaning effort by 40 hours per month. Applied reinforcement learning techniques for optimization tasks, enhancing recommendation efficiency by 20% in simulated environments. Performed A/B testing and statistical analysis to evaluate model performance, boosting deployment strategy and user engagement by 15%. Managed big data processing with Hive and Spark, enabling real-time querying and reducing query response times by 50%.