Hi I am Ankur Singh,
Currently pursuing a Master’s in Software Engineering at SJSU, expecting to graduate in May 2024. Concurrently, I work part-time at Intel as an AI Solutions Engineer. Prior to joining Intel in May 2023, I spent a year as a research assistant under Dr. Wu and Dr. Liu at SJSU Research Foundation, focusing on Federated Learning, Traffic Flow Prediction, and edge deployment.
With 4 years of prior professional experience in AI/ML, Software Engineering, DevOps, Cloud, and Databases, I embarked on my journey by founding AI Adventures, a startup providing AI/ML solutions. Later, as an ML Team Lead at Zoop.One, I orchestrated the successful launch of four ML services, housing 20+ deep learning models, handling over 2M+ requests/month. All this in just ten months. My approach, grounded in first principles, emphasized improving developer experience through process building, establishing best practices, and setting up efficient ML infrastructure, leading to rapid prototyping and significantly reduced Time To Market (TTM). I’m really proud of my work at Zoop.
Beyond my professional endeavors, I am an avid reader and actively participate in competitions, winning multiple Kaggle competitions and hackathons. I’ve contributed to several open-source projects and created two Python packages: colab-everything and torchserve-python, aiming to give back to the community. I aspire to give a talk at a Python Conference someday.
Data Science
85%
Pandas, SQL, BigQuery, PySpark, Sklearn
DL Stack
90%
Pytorch, Fastai, Transformers, PEFT, Accelerate, WandB
LLM Stack
85%
LangChain, LlamaIndex, Pinecone, vLLM, LlamaCPP
MLOps
85%
MLflow, Kubeflow, ONNX, OpenVINO, TorchServe
Programming
90%
OOPs, Design Patterns, Packaging, Unit Testing
CI/CD & DevOps
85%
Git, GitHub Actions, Docker, K8s, AWS, Terraform
Databases
80%
Postgres, SQLite3, MongoDB, Redis, ElasticSearch
API Development & Web-apps
85%
FastAPI, Flask, Firebase, Appwrite, Steamlit, Gradio
Implemented code samples with advanced techniques like QLoRA, RAG, and INT4/8 inference, and developed end-to-end workflows for distributed training and fine-tuning LLMs on Intel hardware. Additionally, I helped maintain AI code samples in the oneAPI Samples repository, showcasing optimization of AI workloads on Intel hardware using Intel's oneAPI toolkits.
Managed deployment of detection and segmentation models on edge devices, optimizing models, and benchmarking on various runtimes. Additionally, helped develop innovative strategies for Knowledge Distillation and Federated Learning, with a focus on regression problems.
Led the development of key ML services, enhancing functionality and performance. Oversaw the team's strategic leadership, launching four ML services in ten months, emphasizing agile and high-performing practices.
Led client project development, overseeing the entire lifecycle and collaborating closely with clients. Created five comprehensive courses covering Python, DS, ML, CV, and DL. Established AI clubs in Pune colleges, fostering a vibrant community through workshops and interactive sessions.