Sweta Pati's Personal Website

Hello! I’m Sweta Pati, an AI/ML Engineer with 5+ years of experience designing, deploying, and scaling solutions in Machine Learning, NLP, Generative AI, RAG, and Agentic AI across domains including FinTech, recruitment, and academic research.

Industry & Research Experience:

I specialize in Machine Learning, LLM fine-tuning, RAG, and Agentic AI systems, industry experience with research-driven innovation to build production-ready AI solutions.

• Currently working as an AI/ML Engineer at 4A Consulting, LLC, where I design modular LLM evaluation systems, implement role-aware prompting strategies, and build scalable GenAI products powering an AI-driven recruitment evaluation platform for multiple Fortune 500 clients.

• As an NLP Engineer at George Mason University, my work on instruction-tuning LLMs for event extraction using annotation guidelines was accepted at ACL 2025 (Findings). I optimized prompt-based EE models using machine-generated annotation guidelines and Python code-style prompts to improve generalization and performance.

• Previously spent 3+ years as an AI/ML Engineer at HighRadius Technologies, where I led ML initiatives that improved fraud detection by 12%, reduced Days Sales Outstanding by 30%, and deployed robust, end-to-end pipelines for global clients like Nestlé, Uber, and Kraft Heinz.

Technical Interests & Expertise:

• Large Language Models (LLMs):
  Fine-tuning and evaluation of models like LLaMA, GPT, and other Transformer-based architectures using techniques such as LoRA, and quantization, instruction tuning, and prompt engineering.

• Generative AI & Agentic Systems:
  Building RAG pipelines, developing Agentic AI frameworks, and leveraging tools like LangChain, Phidata, and agent orchestration for intelligent task automation.

• Machine Learning & NLP Applications:
  Expertise in classification, regression, time series forecasting, event extraction, and deploying solutions for real-world problems in domains across finance, recruitment, and other applied domains.

• MLOps & Scalable ML Engineering:
  Proficient in building CI/CD pipelines, deploying FastAPI-based ML services in Docker containers, and managing cloud infrastructure with AWS, GCP, and Kubernetes for reliable and scalable ML workflows.

I excel at transforming unstructured data into actionable insights.

Education:

I hold a Master’s degree in Computer Science with a specializing in Machine Learning from George Mason University.

Actively Seeking:

I’m actively pursuing full-time opportunities in AI/ML, NLP, or GenAI roles. My goal is to bring research-backed engineering into real-world AI deployments that are scalable, interpretable, and impactful.

Feel free to reach out — I’d love to connect!