Swamy D.

About Me

Machine Learning Engineer with 10 years of experience specializing in developing and deploying cutting-edge AI systems, particularly in ML, NLP, LLM fine-tuning, RAG (Retrieval-Augmented Generation), AI agents, Generative AI (GenAI), and large language models (LLMs). Proven track record in designing, building, and optimizing AI solutions that deliver substantial business value. Swamy D. has experience in feature engineering and feature selection, classification, regression, recommendation systems, clustering, dimensionality reduction, and outlier detection, A/B testing, Learning to Rank (LTR) modeling, Natural Language Processing (NLP), semantic search, vector databases, text classification, sentiment analysis, named entity recognition (NER), and language modeling, Llama, Gemma, Phi, and Zephyr. Proficient in deep learning frameworks (TensorFlow, PyTorch) and NLP-specific libraries (Hugging Face, spaCy, NLTK), along with Scikit-learn, XGBoost, FastAPI and AWS SageMaker. Experienced in containerization technologies like Docker and Kubernetes for packaging and deploying machine learning models.

AI, ML & LLM

Backend

Database

DevOps

Other

Work history

Phenom
Sr. Machine Learning Engineer
2021 - 2025 (4 years)
Remote
  • Fine-tuned large language models (LLMs) such as Zephyr, Phi, Llama, and Gemma for specific HR applications.

  • Developed and deployed LLM-powered solutions for resume parsing, job parsing, profile matching, and candidate matching using foundation models like Zephyr, Phi, Llama, and Gemma.

  • Led a Learning to Rank (LTR) project to enhance job search results for candidates, improving relevance by 15% as measured by Normalized Discounted Cumulative Gain (NDCG)

ZephyrPhi LLaMA Gemma Learning to Rank Normalized Discounted Cumulative Gain XGBoostLambdaMART Multi-Armed Bandit Elasticsearch FastTextUniversal Sentence Encoder BERT BGE AWS Sagemaker
Teradata India Private Limited
Software Engineer (Machine Learning)
2015 - 2021 (6 years)
Remote
  • Developed and implemented machine learning workflows using Teradata's machine learning library to solve a wide range of business problems.

  • Worked on diverse machine learning tasks, including classification, regression, association analysis, recommendation systems, clustering, dimensionality reduction, outlier detection, survival analysis, path analysis, and time series analysis.

  • Collaborated with cross-functional teams to integrate ML solutions into Teradata's data warehouse offerings, enabling seamless data-driven insights for clients.

HadoopHDFS HiveSparkGLM SVM Decision Tree Random Forest AdaBoost XGBoostNaive BayesKNN K-Means NPath CoxPH Attribution modeling Neural NetworksPCA FPGrowth NumpyPandasMatplotlibSeabornTeradata SQL Teradata Aster Analytics

Education

Education
Master of Technology in Computer Science
University of Hyderabad
2013 - 2015 (2 years)