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Hi, I’m Ruchit Patel, a Machine Learning Engineer with over 3 years of experience shaping the end-to-end lifecycle of LLMs and deep learning systems. I enjoy turning research into scalable production solutions, from fine-tuning large language models to building efficient inference stacks and robust data pipelines for computer vision, time-series forecasting, and generative AI. In my recent roles, I led LLM fine-tuning initiatives at Couchbase, built agentic RAG systems with LangChain and Hugging Face models, and implemented MLOps practices with Docker and Kubernetes to improve deployment reliability and reduce costs. I’m passionate about delivering measurable improvements in accuracy, latency, and operational efficiency while collaborating across research, data, and product teams.…Hi, I’m Ruchit Patel, a Machine Learning Engineer with over 3 years of experience shaping the end-to-end lifecycle of LLMs and deep learning systems. I enjoy turning research into scalable production solutions, from fine-tuning large language models to building efficient inference stacks and robust data pipelines for computer vision, time-series forecasting, and generative AI. In my recent roles, I led LLM fine-tuning initiatives at Couchbase, built agentic RAG systems with LangChain and Hugging Face models, and implemented MLOps practices with Docker and Kubernetes to improve deployment reliability and reduce costs. I’m passionate about delivering measurable improvements in accuracy, latency, and operational efficiency while collaborating across research, data, and product teams.

Ruchit Patel

Data Scientist, AI Engineer, Data Analyst, +4

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Hi, I’m Ruchit Patel, a Machine Learning Engineer with over 3 years of experience shaping the end-to-end lifecycle of LLMs and deep learning systems. I enjoy turning research into scalable production solutions, from fine-tuning large language models to building efficient inference stacks and robust data pipelines for computer vision, time-series forecasting, and generative AI. In my recent roles, I led LLM fine-tuning initiatives at Couchbase, built agentic RAG systems with LangChain and Hugging Face models, and implemented MLOps practices with Docker and Kubernetes to improve deployment reliability and reduce costs. I’m passionate about delivering measurable improvements in accuracy, latency, and operational efficiency while collaborating across research, data, and product teams.…Hi, I’m Ruchit Patel, a Machine Learning Engineer with over 3 years of experience shaping the end-to-end lifecycle of LLMs and deep learning systems. I enjoy turning research into scalable production solutions, from fine-tuning large language models to building efficient inference stacks and robust data pipelines for computer vision, time-series forecasting, and generative AI. In my recent roles, I led LLM fine-tuning initiatives at Couchbase, built agentic RAG systems with LangChain and Hugging Face models, and implemented MLOps practices with Docker and Kubernetes to improve deployment reliability and reduce costs. I’m passionate about delivering measurable improvements in accuracy, latency, and operational efficiency while collaborating across research, data, and product teams.

Available to hire

Hi, I’m Ruchit Patel, a Machine Learning Engineer with over 3 years of experience shaping the end-to-end lifecycle of LLMs and deep learning systems. I enjoy turning research into scalable production solutions, from fine-tuning large language models to building efficient inference stacks and robust data pipelines for computer vision, time-series forecasting, and generative AI.

In my recent roles, I led LLM fine-tuning initiatives at Couchbase, built agentic RAG systems with LangChain and Hugging Face models, and implemented MLOps practices with Docker and Kubernetes to improve deployment reliability and reduce costs. I’m passionate about delivering measurable improvements in accuracy, latency, and operational efficiency while collaborating across research, data, and product teams.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Machine Learning Engineer at Couchbase

January 1, 2024 - Present

Led the fine-tuning and deployment of large language models (LLMs), implementing parameter-efficient techniques to improve task-specific performance by 12-18% while reducing fine-tuning costs by 30%. Engineered an agentic RAG system using LangChain and open-source Hugging Face models, improving answer relevance and reasoning accuracy for internal AI assistants by 25%. Architected and optimized the production inference stack, implementing vLLM to reduce average inference latency by 40% and increase throughput by 3.5x. Built a comprehensive evaluation framework to monitor LLM performance across accuracy, latency, and cost, reducing experiment tracking and comparison time by 20%. Drove infrastructure efficiency by redesigning data pipelines for retrieval systems, resulting in $2.5K in monthly infrastructure cost savings. Established MLOps practices by containerizing services with Docker and orchestrating deployments with Kubernetes, improving deployment consistency and reducing environmen

Machine Learning Engineer at West Coast Safety Supply

July 1, 2023 - January 31, 2024

Owned the end-to-end development of a demand forecasting ML pipeline on AWS SageMaker, improving forecast accuracy by 15% compared to previous methods. Integrated Apache Spark for data processing and utilized XGBoost and scikit-learn, reducing prediction error by 12%. Automated the ML lifecycle, implementing scheduled retraining and batch inference workflows using Apache Airflow, which reduced manual retraining effort by 70%. Optimized the cloud infrastructure (AWS EKS, S3, RDS) and ETL processes, leading to an 18% reduction in annual operational spend. Led DevOps initiatives for the ML team, introducing GitHub Actions CI/CD and infrastructure-as-code with Terraform, reducing deployment failures by 25%.

Machine Learning Engineer at Syngenta

June 1, 2022 - May 31, 2023

Redesigned a production computer vision pipeline for aerial drone imagery, improving inference speed by 35% by transitioning between TensorFlow and PyTorch to leverage models like ResNet and YOLO. Engineered data preprocessing workflows, reducing data preparation time by 20% through standardizing image augmentation and validation splits. Researched and integrated advanced architectures, including early prototypes of Vision Transformers, achieving a 10% improvement in accuracy for detecting early crop stress indicators. Developed a foundational MLOps platform, automating the model lifecycle and reducing the time from model training to deployment from several days to under 4 hours. Collaborated with domain experts to translate agronomic requirements into model specifications, achieving 95% alignment between model outputs and expert validation.