Performance-driven Machine Learning Engineer with over 5 years of experience building production AI systems and internal agent infrastructure. Proven ability to develop automated Large Language Model (LLM) workflows and agentic tools that enhance engineering productivity and streamline the Software Development Life Cycle (SDLC). Experienced in model selection, benchmarking, and operating end-to-end AI stacks to deliver high-impact results in fast-paced environments. Committed to supporting technical teams by implementing cutting-edge AI developer tools and instrumentation to measure velocity gains.
Performance-driven Machine Learning Engineer with over 5 years of experience building production AI systems and internal agent infrastructure. Proven ability to develop automated Large Language Model (LLM) workflows and agentic tools that enhance engineering productivity and streamline the Software Development Life Cycle (SDLC). Experienced in model selection, benchmarking, and operating end-to-end AI stacks to deliver high-impact results in fast-paced environments. Committed to supporting technical teams by implementing cutting-edge AI developer tools and instrumentation to measure velocity gains.
• Developed a benchmarking framework to evaluate model configurations using vLLM, improving response accuracy by 25% across domain-specific queries. • Built an agentic AI assistant integrating OpenAI and Anthropic APIs with Pydantic for robust data validation and multi-agent orchestration. • Implemented session-based memory and dynamic prompt engineering to improve the reliability and context-awareness of internal system workflows.