# Srivathsan Sundaresan

> AI Infrastructure & Data Engineer | Butlr | USC

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/srivathsan

I’m an AI Infrastructure and Data Engineer with 5+ years of experience building scalable ETL pipelines, distributed systems, and machine learning platforms. My work focuses on event-driven architectures, cloud orchestration, CI/CD for ML, and deploying inference systems from edge to cloud.

I enjoy owning problems end-to-end, from data ingestion and processing to model deployment and production reliability, helping teams turn data and ML systems into real-world impact.

Email: srivathsan.sundaresan@gmail.com

## Work Experience
### Senior Software Engineer @ Butlr
Jan 2024 – Present
-  Optimized cloud infrastructure, reducing costs from $250k/month (8,000 sensors) to $100k/month (13,000+ sensors)
- Developed AWS ECS applications using Terraform for infrastructure provisioning and Azure Kubernetes Service with Docker for efficient
containerization.
- Built and deployed CI/CD pipelines for sensor occupancy applications, integrating Prometheus for monitoring and Grafana for analytics.
- Engineered real-time data streaming pipelines, directing ~100GB/day to InfluxDB for analytics and AWS S3 for cost-effective storage.
- Worked with big data formats (Avro, Parquet) for Machine Learning Engineering tasks.

### Applied Scientist II @ Butlr
Jan 2022 – Jan 2025 | San Francisco Bay Area
- Architected and operated 6 production Ray clusters (detections, headcount, occupancy, care, room motion,
visualizer) across multi-AZ AWS, supporting 100+ concurrent worker nodes and autoscaling from zero to 1,000
workers via Ray Autoscaler. Deployed Ray Serve for low-latency HTTP inference, running continuously in
production for 2+ years.
- Designed a distributed stream processing framework using Ray’s actor model to ingest NATS message
streams, implement priority-based queuing, and dynamically schedule distributed processors—automatically
scaling concurrent workers to handle data from thousands of devices.
- Built versioned Ray cluster deployment pipelines with templated configs, automated job submission, and
rollback support. Integrated full-stack observability using Prometheus, Ray’s metrics API, Grafana, and
CloudWatch with custom counters, gauges, and latency histograms.
- Developed models for detection, tracking, motion detection, pose estimation and successfully deploying them end-to-end for ~5000 sensors
- Achieved 92% accuracy in person detection and counting using OpenCV for low-resolution thermal data.

### Machine learning Scientist @ Butlr
Jan 2020 – Jan 2022 | San Francisco Bay Area
- Developed quantized people-tracking models for edge deployment using TensorFlow Lite on Coral Edge TPU.
- Specialized in IoT communication protocols (MQTT) for seamless sensor-to-cloud data transmission, while maintaining and scaling servers.

### Software Engineer Intern (Computer Vision) @ Snap Inc.
Jan 2020 – Jan 2020 | Los Angeles Metropolitan Area
- Developed deep learning models using PyTorch with optimized backbone architectures for efficient execution on mobile devices.
- Led end-to-end dataset preprocessing, model training, and evaluation.

### Graduate Research Assistant SAIL Lab @ University of Southern California
Jan 2019 – Jan 2020 | Greater Los Angeles Area
Working in SAIL lab in USC on a Natural language processing task: Movie summarization
Converting movie scripts into Wikipedia like plot summaries

### Research Intern - MILE Lab @ Indian Institute of Science (IISc)
Jan 2017 – Jan 2017 | Bangalore
Worked under the guidance of Dr. A G Ramakrishnan, Chairman, Dept of Electrical Engineering
August-December 2017
Voice Activity Detection from the breathing pattern of a speaker

May-July 2017
Performed Dictionary based source separation code to enhance noisy speech and evaluated the perceptive quality improvement for people with hearing aid/disability

### Summer Research Intern - LEAP Lab @ Indian Institute of Science (IISc)
Jan 2016 – Jan 2016 | Bengaluru Area, India
Worked under the guidance of Dr. Sriram Ganapathy, Assistant Professor, Dept of Electrical Engineering
Project: Height Estimation from short instances of speech


## Contact & Social
- LinkedIn: https://linkedin.com/in/srivathsan-sundaresan

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Source: https://flows.cv/srivathsan
JSON Resume: https://flows.cv/srivathsan/resume.json
Last updated: 2026-03-29