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Sai Aravind Sreeramadas

@saiaravindsreeramada

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I build production LLM, RAG, and generative AI systems that improve enterprise decisions and workflows.

Canada

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What I'm looking for

I'm looking to lead end-to-end LLM, RAG, and agentic AI initiatives that turn applied research into scalable enterprise products, while mentoring teams and partnering closely with product and engineering.

I'm leading Agentic AI initiatives at BenchSci for pharmaceutical R&D, including an evaluation framework for a QA system processing 4TB+ of scientific literature that helped unblock a $3M+ Thermo Fisher partnership deployment.

Previously at Relativity, I led generative AI, retrieval, and recommendation systems for legal and compliance products used by 50,000+ daily users. I led and mentored four applied scientists and engineers while taking systems from research through production.

I built ChatGPT-based document classification that reduced manual review from weeks to under 24 hours, created evaluation frameworks that cut deployment cycles from three weeks to one, and architected a multi-task RAG pipeline across 1M+ documents.

My work also spans solar forecasting at HydroQuebec and ML automation at Qualcomm, where I improved operational forecasts, reduced test-suite runtime, and scaled ticket deduplication. I focus on turning advances in LLMs, retrieval, and ML systems into reliable products with measurable business impact.

Experience

Work history, roles, and key accomplishments

Current

Senior Machine Learning Engineer

Current

BenchSci

Oct 2025 - Present (11 months)

Leading Agentic AI initiatives for pharmaceutical R&D, architecting evaluation frameworks and systems that unlocked revenue and accelerated model deployment for top-tier clients.

Agentic AI LLM Evaluation RAG Python PyTorch Lang Chain AWS Kubernetes Docker

Senior Applied Scientist

Relativity

Jun 2022 - Sep 2025 (3 years 3 months)

Led design, deployment, and adoption of generative AI systems for legal/compliance software, driving standards across product lines used by 50,000+ daily users. Mentored a team of 4 Applied Scientists and Engineers.

Generative AI RAG LLM Evaluation GPT 4 PyTorch Hugging Face Lang Chain Faiss AWS Kubernetes Docker Airflow MySQL MongoDB Elastic

Research Intern

HydroQuebec

Jul 2021 - Jan 2022 (6 months)

Improved CNN-LSTM solar time-series forecasting models with UNet-style architecture, boosting accuracy for +6-hour predictions while halving model size. Operational deployment generated $2M/year savings in energy trading.

CNN LSTM Time series Forecasting Python PyTorch

ML Engineer

Qualcomm

Jun 2018 - Aug 2021 (3 years 2 months)

Transitioned from contractor to full-time team member on a newly established machine learning team, focusing on testing Wi-Fi software integration and automating processes for software release.

SBERT NER Seq2Seq Python Machine Learning Automation

Software Engineer, Machine Learning

Eximius Design

Nov 2017 - Jun 2018 (7 months)

Developed multimodal parsing system combining OCR with NLP models, achieving 95% table extraction accuracy. Deployed edge ML models for real-time mobile inference.

OCR NLP Multimodal AI Edge AI Python