ML Engineer specializing in large-scale inference platforms, generative AI, and distributed systems. Currently building ML infrastructure for Adobe Firefly's generative AI workloads. Published researcher in Graph Neural Networks and bias mitigation.
Education 🎓
- MS in Computational Data Science — Indiana University, Bloomington (2023) • GPA: 3.87/4.0
- BS in Computer Science — National Institute of Technology, Patna (2015) • GPA: 8.32/10.0
Current Work 💼
- Machine Learning Engineer 4 @ Adobe (Jul 2024 - Present)
- Architecting ML inference platform for Firefly's generative AI serving billions of video/image workloads
- Building distributed inference framework with vLLM, Ray Serve, and TensorRT-LLM for multi-billion parameter LLMs
Previous Experience
- Senior Software Engineer @ EvolutionIQ (2023-2024) — Data pipelines for NLP, generative AI at intersection of fintech & healthcare
- Software Dev Engineer II @ Swiggy (2019-2021) — Led Data Acquisition Platform processing 15M rows/day; built Feature Store serving 10K QPS
- Software Dev Engineer @ Flipkart (2017-2019) — Search relevance & ML Ops; first automated ML deployment workflow; Hackday 9 Winner
- Software Engineer @ Groupon, NetSpeed Systems (2015-2017) — Backend engineering & SOC simulation
Research 📄
- First Author — "Biased Contrastive Learning debiases Graph Neural Networks" (NetSci 2023, IC2S2 2023)
ML Inference & Serving: vLLM • Ray Serve • Ray Data • TensorRT-LLM • Triton Inference Server
ML/AI: PyTorch • PyTorch Lightning • PyTorch Geometric • TensorFlow • Scikit-learn • LLMs • GNNs • NLP • Computer Vision
Data Engineering: Apache Spark • Apache Kafka • Apache Flink • Hadoop HDFS • Airflow • Feature Stores
Languages: Python • Scala • C++ • SQL • Java
Cloud: AWS SageMaker • AWS DynamoDB • GPU Clusters • Docker • Kubernetes
🌐 Portfolio: thunderock.github.io