Prudhvi Raj

Senior AI & ML Systems Engineer with 6+ years of experience designing, deploying, and scaling production-grade ML systems and LLM-driven applications. Strong expertise in evaluation frameworks, model reliability, distributed backend architecture, and performance optimization. Proven ability to translate ambiguous problem statements into measurable, scalable systems with strong business impact. Experienced in owning full lifecycle delivery from experimentation to production monitoring.

Senior AI & Backend Engineer - Turing

(2024-12)

• Engineered high-throughput ML inference infrastructure serving over 1M requests per day with 99.9% service availability.
• Re-architected request processing using asynchronous execution and Redis caching, cutting p95 latency by 40%.
• Developed a production churn prediction model achieving 0.89 ROC-AUC and driving measurable retention improvements.
• Built a structured evaluation pipeline for LLM outputs with rubric-based scoring across correctness, reasoning, and completeness.
• Enforced strict JSON schema validation and response contracts, reducing malformed output rates by 75%.
• Implemented real-time drift detection with automated retraining workflows to prevent long-term model degradation.
• Optimized CI/CD pipelines, shrinking deployment turnaround from 45 minutes to under 10 minutes.
• Conducted system design reviews and guided 4 engineers on scalable ML system patterns.

Software Development Engineer - Google

(2022-06 - 2024-12)

• Designed and maintained backend services supporting 50k+ daily transactions.
• Refactored batch processing jobs, improving execution time by 60%.
• Redesigned indexing strategies and query structures, cutting database latency by 70%.
• Integrated statistical modeling workflows from SAS into Python-based ML pipelines.
• Applied transformer-based NLP techniques for summarization and QA use cases using prompt optimization strategies.

Software Development Engineer - Google

(2019-06 - 2022-05)

• Built robust ETL pipelines integrated with Azure Data Lake and Synapse for large-scale data processing.
• Developed early-stage ML and data solutions that later scaled into production platforms.
• Worked across backend services, data processing, and automation.
• Implemented data validation and pipeline monitoring mechanisms to ensure reliability across production workflows.
• Recognized for high ownership, fast execution, and strong problem-solving ability.

Bachelor of Technology - EEE - SV Colleges of engineering (2016)