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Software Engineer with a Master’s degree in Computer Science and 3+ years of experience building AI systems and scalable distributed infrastructure. Skilled in Python, RAG, agentic AI, and model evaluation. Experienced in production ML pipelines and cloud deployments across GCP and AWS, with hands-on work across distributed training/inference, retrieval optimization, and evaluation using frameworks like Ragas and OpenEvals.…Software Engineer with a Master’s degree in Computer Science and 3+ years of experience building AI systems and scalable distributed infrastructure. Skilled in Python, RAG, agentic AI, and model evaluation. Experienced in production ML pipelines and cloud deployments across GCP and AWS, with hands-on work across distributed training/inference, retrieval optimization, and evaluation using frameworks like Ragas and OpenEvals.

Aditya Dawadikar

Software Engineer, AI Engineer, Data Scientist, +2

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Software Engineer with a Master’s degree in Computer Science and 3+ years of experience building AI systems and scalable distributed infrastructure. Skilled in Python, RAG, agentic AI, and model evaluation. Experienced in production ML pipelines and cloud deployments across GCP and AWS, with hands-on work across distributed training/inference, retrieval optimization, and evaluation using frameworks like Ragas and OpenEvals.…Software Engineer with a Master’s degree in Computer Science and 3+ years of experience building AI systems and scalable distributed infrastructure. Skilled in Python, RAG, agentic AI, and model evaluation. Experienced in production ML pipelines and cloud deployments across GCP and AWS, with hands-on work across distributed training/inference, retrieval optimization, and evaluation using frameworks like Ragas and OpenEvals.

Available to hire

Software Engineer with a Master’s degree in Computer Science and 3+ years of experience building AI systems and scalable distributed infrastructure. Skilled in Python, RAG, agentic AI, and model evaluation.

Experienced in production ML pipelines and cloud deployments across GCP and AWS, with hands-on work across distributed training/inference, retrieval optimization, and evaluation using frameworks like Ragas and OpenEvals.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

Aragonese

Intermediate

Javanese

Intermediate

Work Experience

AI Research Assistant at San Jose State University, Dept of Computer Science

August 1, 2025 - Present

Developed an activation norms guided metric for selective LoRA fine-tuning of LLMs, improving training wall-clock speed and inference latency. Deployed A100 GPU clusters and created automation for distributed training (DDP) and tensor-parallel inference (TP). Used QLoRA and ZeRO for memory reduction and FlashAttention for faster training/inference in resource-constrained environments.

Applied AI Engineer at Quantiphi Analytics Solutions Pvt. Ltd.

January 1, 2022 - April 1, 2024

Built an event-driven OCR ingestion pipeline on Vertex AI using Apache Spark, Pub/Sub, and BigQuery to digitize and backfill a 5-year backlog of 50,000+ documents in under 6 hours. Engineered a 6-stage Spark ETL pipeline achieving ~1,200 records/minute for validation, normalization, and reference enrichment before loading curated datasets into BigQuery. Led an internal Human-in-the-Loop platform (React/TypeScript/Python) for analyst validation of low-confidence OCR outputs, with automated dataset versioning and model retraining via Vertex AI SDK and BigQuery. Implemented workflow tracking with outbox tables and event queues for end-to-end traceability and operational observability using Logging, Prometheus, and Grafana. Built Git-based CI/CD for automated Docker builds and deployments to Cloud Run with unit and end-to-end validation.