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chejarla chaitu

@chejarlachaitu

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Senior AI/ML engineer focused on Generative AI, LLMs, and edge MLOps.

India

Message

What I'm looking for

I’m looking for a role where I can build production-grade GenAI/LLM and agentic systems—optimized for latency, cost, and energy—across cloud and edge, with strong MLOps (MLflow/CI-CD) and measurable impact.

I’m a Senior AI/ML Engineer with 6+ years of experience designing and deploying scalable deep learning, generative AI, and edge AI solutions across cloud and resource-constrained environments. I specialize in Generative AI and LLM ecosystems, building production-grade applications with RAG pipelines and multi-agent systems.

Across my roles, I’ve optimized AI models for performance, latency, and energy efficiency—working hands-on with neuromorphic computing and hardware-aware deployment. I’ve built end-to-end ML systems and MLOps workflows, including model development, evaluation, deployment, and monitoring using MLflow, CI/CD pipelines, and cloud platforms like AWS, GCP, and Azure.

I enjoy connecting AI to real business outcomes through intelligent automation, data pipelines, dashboards, and workflow systems. From enterprise GenAI solutions using LangChain and OpenAI APIs to on-device RAG and predictive monitoring on Akida SoC, I focus on reliability, robustness, and measurable deployment impact.

Experience

Work history, roles, and key accomplishments

Current

Senior Machine Learning Engineer

Current

Motivity Labs

Jan 2026 - Present (5 months)

Contributed to a large-scale RAG project by building and managing SQL-based data workflows for processing, analytics, and dashboarding. Developed AI-powered medical and psychological chatbot experiences and worked on agent-based multi-reasoning systems for contextual, real-time responses.

SQL Workflows Data & Analytics Dashboards Agentic AI Multi Agent Systems Conversational AI

Data Scientist – GenAI

TrueTek Consulting

Nov 2024 - Nov 2025 (1 year)

Built structured support and customer onboarding solutions to improve deployment efficiency and client adoption. Designed, fine-tuned, and deployed domain-specific LLM solutions with LangChain and OpenAI APIs, optimizing end-to-end pipelines for latency, cost, and accuracy on AWS/Azure.

LLMs (LangChain OpenAI API Fine Tuning Prompt Engineering Cost Optimization AWS Azure

Solutions Architect

BrainChip Inc

Mar 2022 - Oct 2024 (2 years 7 months)

Designed and deployed neuromorphic and transformer-based AI models on Akida SoC for real-time, low-power intelligence, including converting CNNs to spiking neural networks with <38 μJ per inference. Built on-device RAG-based systems for real-time summarization and event detection and developed automated benchmarking and failure-mode analysis to improve production reliability.

Akida SoC Pruning On Device RAG TENNs MLFlow Benchmarking PyTorch

Data Engineer

N.V. Data Systems

May 2017 - Oct 2019 (2 years 5 months)

Developed fraud risk and fraud detection models using large insurance datasets, including XGBoost, Random Forest, and Logistic Regression, improving fraud identification rates by 18%. Built NLP-based claim text classification that improved categorization accuracy by 30% and delivered time-series forecasting for loss ratio prediction with a 40% improvement in financial risk planning.

Fraud Detection XGBoost Random Forest Logistic Regression GLM Hypothesis Testing Time Series EDA