Valli

Machine Learning Engineer with 4+ years of experience building scalable AI microservices and REST APIs for 2M+ users. Skilled in GenAI/LLMs, agentic systems, and RAG pipelines using Neo4j and vector databases (Redis, Elasticsearch).

Software Engineer – AI/ML - Sling Media (Dish Network) - Denver, CO

(2024-10)

Spearheaded AI/ML integration and scalable microservices for a premier live TV platform (2M+ subscribers) to enhance UI performance and backend reliability across 14+ platforms.

• Agentic AI Reasoning: Architected an agentic AI system utilizing LLM-based reasoning for autonomous video asset validation and self-correcting media pipelines.
• ML Microservices: Developed and orchestrated distributed Python (FastAPI, Django) and Node.js microservices on GCP and AWS to support real-time inference for 2M+ users.
• Intelligent Discovery: Integrated Vector Search (Elasticsearch, Redis) and Neo4j Graph DB to build real-time recommendation models, driving a 20% increase in user engagement.
• Performance Engineering: Realized a 3x system efficiency gain and reduced application load times by 7 seconds through multiprocessing and parallel execution.
• API Architecture: Designed scalable RESTful APIs and backend logic to enhance UI performance and backend reliability across 14+ platforms.

Python Developer / Engineering Analyst - Oceaneering - Pune, India

(2022-04 - 2024-01)

Optimized subsea engineering systems through automated data processing, structural analysis, and the development of predictive ML models.

• Predictive ML & Maintenance Engineering: Developed Python-based ML models for predictive maintenance and equipment failure analysis using telemetry and sensor data, achieving 85% accuracy and a 20% reduction in operational downtime.
• Scalable Data Pipelines & Cloud Integration: Designed containerized data processing pipelines in Kubernetes and GCP to clean, preprocess, and transform structured and unstructured engineering data for ML model training and efficient simulation data serving.
• Graph-Based Knowledge Systems (RAG): Implemented Redis as a vector store and Neo4j graph DB to model complex engineering relationships and support RAG-style knowledge queries, improving subsea riser system reliability by 25%.
• AI-Driven Visualization & Monitoring: Built React.js web interfaces and Flask REST APIs to visualize telemetry and ML predictions from GCP pipelines, reducing anomaly detection time by 35% through real-time operational insights.

Python Developer (Internship to FT) - NSG Hyderabad - Hyderabad, India

(2019-07 - 2020-12)

Focused on full-stack application development and deployment automation within a LAMP and Django environment.

• E-commerce AI & Analytics: Deployed a Machine Learning-based recommendation engine that boosted user conversion rates by 35% using real-time behavior analytics.
• Backend Engineering & Scalability: Built complex application logic and backend systems using Python and Django, utilizing optimized SQL queries and DynamoDB for high-volume data processing and REST API development.
• Task Scheduling & Cloud Automation: Designed and implemented a DynamoDB-based job scheduling system and automated deployment pipelines, reducing manual scheduling overhead by 30%.
• Data Transformation & Quality Assurance: Developed XML data transformation scripts and implemented comprehensive unit testing using PyUnit to ensure 100% production stability.

M.S. - Engineering - Indian Institute of Technology Madras (2023-07)

B.Tech. - Engineering - Indian Institute of Information Technology-RGUKT (2017-05)