SANDEEP KETHIREDDY
Greater Tampa Bay Area | sandzco@gmail.com | 860 997 6119 | linkedin.com/in/sandeepkethireddy
AI/ML Engineering Manager | Solutions Architect
Technical leader with 15+ years of experience building and scaling AI/ML solutions and leading high-performing engineering teams. Proven track record delivering production LLM applications, autonomous AI agents, and ML-powered systems that drive measurable business outcomes. Expert in Python-based ML frameworks, RAG systems, LLM fine-tuning, and cloud-native architectures. Currently leading cross-functional teams in developing enterprise AI solutions with $25M+ in projected annual savings.
LEADERSHIP & AI/ML IMPACT
• Lead 4-engineer team across onshore/offshore locations, driving AI/ML best practices, code quality standards, and agile development workflows
• Architected 3 production-ready AI/ML systems generating estimated $25M+ in annual cost savings across operations, supply chain, and customer support
• Spearheaded enterprise-wide ML adoption through development of self-service ML platform serving 50+ business users
• Drive technical strategy for AI/ML initiatives, including model selection, architecture design, deployment pipelines, and MLOps infrastructure
• Mentor engineering teams on modern ML practices: model training, evaluation, fine-tuning, prompt engineering, and production deployment
KEY AI/ML INITIATIVES
• Autonomous Agent Framework: Multi-agent orchestration system using LangChain and LangGraph with tool-calling capabilities, ReactJS framework for reasoning, and custom workflow automation processing 10K+ queries daily
• RAG-Powered Customer Support: Vector-based retrieval system leveraging Pinecone embeddings and semantic search, achieving 60% improvement in response accuracy and 50% reduction in query resolution time
• Demand Forecasting ML System: Ensemble modeling approach (Random Forest + XGBoost) integrating manufacturing capacity and lead time variables, boosting production scheduling efficiency by 40%
• Domain-Specific LLM Fine-tuning: LoRA/QLoRA optimization of Llama 2 and Mistral models for manufacturing compliance and technical documentation, achieving 40% accuracy improvement with 60% cost reduction through 4-bit quantization
• Enterprise ML Platform: Self-service platform (ReactJS + Python FastAPI) enabling automated feature engineering, hyperparameter tuning with Optuna, and model versioning with MLflow, reducing model development cycles from weeks to hours
TECHNICAL PROFICIENCIES
AI/ML Tools: 
PyTorch, TensorFlow, Scikit-Learn, HuggingFace Transformers, LangChain, LangGraph, AutoGen
LLM Technologies:
OpenAI GPT-4, Anthropic Claude, Llama 2/3, Mistral, QLoRA fine-tuning, PEFT, prompt Engg.
ML Operations:
MLflow, Weights & Biases, model versioning, A/B testing, feature stores, hyperparameter tuning (Optuna)
Vector Databases
Pinecone, Chroma, Weaviate, FAISS; Embeddings: OpenAI, Sentence Transformers
Programming
Python, Java, JavaScript/NodeJS, C#, PL/SQL, Swift/Objective-C, Unix/Bash, 
Frameworks: 
Spring Boot, .NET, FastAPI/Starlette, Django, Flask, ReactJS, Android, iOS
Databases & Q’s:
Oracle, MSSQL, PostgreSQL, MySQL, Snowflake, MongoDB, Redis, Kafka, RabbitMQ
Integration/Testing: 
Mulesoft, SSIS, Selenium, jUnit, Pytest, Apache JMeter, Postman. 
DevOps:
Docker, Kubernetes, Jenkins, CI/CD, Git/GitHub, Maven, Gradle
Cloud Platforms: 
AWS (SageMaker, Lambda, EC2, S3), Azure, GCP
PROFESSIONAL EXPERIENCE
Regal Rexnord – Grafton, WI	2018 to Present
AI/ML Engineering Lead / Solutions Architect
• Lead cross-functional team of 4 engineers (onshore/offshore), conducting code reviews, sprint planning, and technical mentorship while aligning development activities with strategic AI/ML initiatives
• Architected and deployed production LLM applications with autonomous AI agents using LangGraph and ReactJS frameworks, implementing multi-step reasoning workflows processing 10K+ queries daily with 50% faster response times and 85% task completion accuracy
• Implemented RAG-powered customer support chatbot leveraging Pinecone vector database and OpenAI embeddings for enhanced semantic search, improving knowledge base query accuracy by 60% and reducing average response time from 5 minutes to 2 minutes
• Developed autonomous AI agents capable of multi-step reasoning for automated workflow orchestration, integrating with internal APIs and databases for real-time decision-making in manufacturing operations
• Fine-tuned Llama 2 (7B) and Mistral (7B) models using LoRA/QLoRA techniques for domain-specific manufacturing compliance and technical documentation generation, achieving 40% improvement in domain accuracy while reducing inference costs by 60% through 4-bit quantization
• Built ML-powered demand forecasting system using ensemble methods (Random Forest + XGBoost + LSTM) that predicts optimal manufacturing schedules by integrating capacity constraints and lead time variables, boosting production line scheduling efficiency by 40% and reducing stockouts by 25%
• Engineered enterprise ML platform with ReactJS frontend and Python FastAPI backend, enabling 50+ non-technical users to perform automated feature engineering, model training with hyperparameter tuning (Optuna), and batch predictions. Integrated MLflow for model versioning and experiment tracking
• Designed and developed native mobile applications for iOS (Swift) and Android (Java) to enable secure real-time transactions against on-premises ERP systems, improving field operations efficiency by 30% and reducing data entry errors by 45%
• Led Visual Compliance integration project, orchestrating REST API implementation for real-time customer screening during order entry, streamlining compliance workflows and reducing processing time by 40%
• Established robust CI/CD pipelines using Jenkins and GitHub Actions for automated testing, building, and deployment of ML models and applications, reducing deployment time from days to hours
Environment: AWS (SageMaker, Lambda, S3, EC2), Azure, Python, PyTorch, Scikit-Learn, LangChain, LangGraph, HuggingFace Transformers, OpenAI/Anthropic APIs, LoRA/QLoRA, Vector Databases (Pinecone, Chroma), MLflow, Optuna, NLP, RAG, Java, ReactJS, FastAPI, Oracle, MSSQL, Databricks, Mulesoft, Redis, Docker, Kubernetes, Jenkins, Git/GitHub
Fortive – Everett, WA	2010 to 2018
Senior Software Engineer
• Designed and developed integrations with third-party SaaS systems to facilitate seamless import/export of master data, ensuring data flow resilience and high availability across enterprise platforms
• Provided comprehensive system support including debugging, maintenance, and issue resolution for critical production systems, maintaining 99.5% uptime and rapid incident response
• Led transformation of batch processing systems into real-time microservice-based REST APIs using Spring Boot, improving data accessibility by 60% and reducing processing latency from hours to seconds
• Developed Python Flask backend and ReactJS-based shipping portal for rate comparison across multiple carriers within FreightPop TMS, utilizing cx_Oracle drivers for Oracle Ship Confirm API integration and implementing Okta SSO for secure authentication
• Architected and implemented REST API integrations between SciQuest SaaS procurement platform and on-premises ERP systems using Spring Boot middleware, processing 100K+ transactions monthly
• Migrated critical applications to AWS cloud-native services (Lambda, RDS, S3, CloudWatch), resulting in 35% reduction in hosting costs and 15% increase in application availability through auto-scaling and multi-AZ deployment
Environment: AWS, Java/J2EE, Spring Boot, Python, Flask, JavaScript, ReactJS, PL/SQL, Oracle EBS 11i, MemCached, MySQL, SQLite, Unix Scripting, ASP.NET, SSIS, SQL Server, Git/GitHub
EARLIER CAREER
Principal Software Consultant | Empowered Solutions – Plano, TX (2009-2010): Partnered with Fortune 500 clients including US Steel Corporation, Pacific Scientific, and Danaher Motion to automate workflows, implement custom Oracle ERP-based solutions, and deliver business-critical enterprise applications using Java/J2EE, Python, Oracle, and Unix scripting.
Additional Experience (2005-2009): Software Consultant roles at Baytree Associates (NY), IT Convergence (SF), and Nettlinx Inc (NJ), delivering Oracle ERP implementations, eCommerce solutions, and Procure-to-Pay automation for clients including Continuum Health Partners, Beckman Coulter, and Acuity Brands.
EDUCATION & CERTIFICATIONS
Bachelor of Engineering in Electronics & Communications | St. Josephs College of Engineering, Chennai, India
Master of Science in Electrical Engineering | University of Hartford, Hartford, CT
AWS Solutions Architect Associate SAA-C03 Certification*
Complete A.I. & Machine Learning, Data Science Bootcamp (Udemy, 2021)
LLM Engineering Specialization - Generative AI, RAG & AI Agents (Udemy, 2023)
WEBSITES & LINKS
https://sandzco-ai.web.app 
https://github.com/sandzco 
www.linkedin.com/in/sandeepkethireddy