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saurya koka

@sauryakoka

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AI/ML Software Engineer building reliable Python backends, production ML systems, and agentic AI applications.

India

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What I'm looking for

I’m looking to build reliable AI and backend products where I can own meaningful parts of the system end to end, from model or agent logic through APIs, evaluation, deployment, observability, and performance.

I’m an AI/ML Software Engineer with 2+ years of experience building production ML systems, Python backend services, and AI applications across healthcare and agentic systems.

At Charles River Medical Center, I built and validated TensorFlow models on noisy clinical data, reaching 92% validation accuracy, and optimized NVIDIA Jetson inference to improve throughput by 35%. At L.V. Prasad Eye Institute, I worked on containerized FastAPI inference services, PostgreSQL logging, AWS infrastructure, and CI/CD, including systems running at sub-150 ms latency.

More recently, I built PlanPilot independently, an agentic AI and RAG planning system using Python, FastAPI, LangGraph, OpenAI APIs, ChromaDB, structured outputs, validation guardrails, tracing, and a 50-test pytest suite.

I’m especially interested in remote roles across Applied AI, AI Engineering, Machine Learning, backend AI systems, and production GenAI where I can own real systems end to end and work on reliability, evaluation, deployment, and product impact.

Experience

Work history, roles, and key accomplishments

ML Engineer

Charles River Medical Center

Mar 2025 - Jun 2026 (1 year 3 months)

Developed and validated a TensorFlow CNN pipeline on noisy clinical data, achieving 92% validation accuracy. Optimized NVIDIA Jetson inference, increasing throughput by 35% and reducing dataset variability by 30%.

TensorFlow CNN Python Precision Recall F1 Score Cross Validation NVIDIA Jetson Inference Optimization data preprocessing Augmentation

Machine Learning Engineer

L.V. Prasad Eye Institute

Sep 2023 - Aug 2024 (11 months)

Built and tested a containerized FastAPI inference service under concurrent workloads, achieving sub-150 ms latency and improving failure visibility. Provisioned AWS infrastructure and automated CI/CD workflows with GitHub Actions.

fastAPI Docker PostgreSQL REST APIs EC2 AWS IAM S3 GitHub Actions CI CD SQL Containerization Cloud Native ML Inference

Software Engineering Intern

National Informatics Centre

Sep 2022 - Jul 2023 (10 months)

Maintained 99% service availability using structured logging, retry logic, exception handling, and regression testing across Django and SQL services. Refactored Python backend modules and test workflows, reducing processing inconsistencies by 15% while achieving 95% document-processing accuracy.

Django SQL Python Structured logging Retry Logic Exception Handling Regression Testing