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Machine Learning and AI Engineer with 3+ years of experience designing, developing, and deploying scalable machine learning, deep learning, and Generative AI solutions across enterprise environments. Expertise in Python, PyTorch, TensorFlow, Scikit-learn, LLMs, and MLOps, with hands-on building end-to-end ML pipelines and production AI applications. Delivered AI platforms processing 500K+ daily records, improving model performance by 35%, and reducing inference latency by 25%. Developed enterprise GenAI solutions achieving 98% accuracy while automating manual effort through intelligent decision support and evaluation-driven iteration.…Machine Learning and AI Engineer with 3+ years of experience designing, developing, and deploying scalable machine learning, deep learning, and Generative AI solutions across enterprise environments. Expertise in Python, PyTorch, TensorFlow, Scikit-learn, LLMs, and MLOps, with hands-on building end-to-end ML pipelines and production AI applications. Delivered AI platforms processing 500K+ daily records, improving model performance by 35%, and reducing inference latency by 25%. Developed enterprise GenAI solutions achieving 98% accuracy while automating manual effort through intelligent decision support and evaluation-driven iteration.

Manan Agrawal

AI Engineer, AI Developer, AI Prompt Engineer, +1

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Machine Learning and AI Engineer with 3+ years of experience designing, developing, and deploying scalable machine learning, deep learning, and Generative AI solutions across enterprise environments. Expertise in Python, PyTorch, TensorFlow, Scikit-learn, LLMs, and MLOps, with hands-on building end-to-end ML pipelines and production AI applications. Delivered AI platforms processing 500K+ daily records, improving model performance by 35%, and reducing inference latency by 25%. Developed enterprise GenAI solutions achieving 98% accuracy while automating manual effort through intelligent decision support and evaluation-driven iteration.…Machine Learning and AI Engineer with 3+ years of experience designing, developing, and deploying scalable machine learning, deep learning, and Generative AI solutions across enterprise environments. Expertise in Python, PyTorch, TensorFlow, Scikit-learn, LLMs, and MLOps, with hands-on building end-to-end ML pipelines and production AI applications. Delivered AI platforms processing 500K+ daily records, improving model performance by 35%, and reducing inference latency by 25%. Developed enterprise GenAI solutions achieving 98% accuracy while automating manual effort through intelligent decision support and evaluation-driven iteration.

Available to hire

Machine Learning and AI Engineer with 3+ years of experience designing, developing, and deploying scalable machine learning, deep learning, and Generative AI solutions across enterprise environments. Expertise in Python, PyTorch, TensorFlow, Scikit-learn, LLMs, and MLOps, with hands-on building end-to-end ML pipelines and production AI applications.

Delivered AI platforms processing 500K+ daily records, improving model performance by 35%, and reducing inference latency by 25%. Developed enterprise GenAI solutions achieving 98% accuracy while automating manual effort through intelligent decision support and evaluation-driven iteration.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

Javanese

Intermediate

Work Experience

AI Research & Development Associate at Martinrea International US Inc.

August 1, 2025 - May 1, 2026

Architected and deployed scalable machine learning and Generative AI solutions to transform enterprise idea intelligence, automate analytics workflows, and improve operational decision-making across business teams. Designed and implemented end-to-end ML pipelines (data ingestion, feature engineering, training, validation, deployment, monitoring) processing 500K+ records daily using Python, MLflow, Azure SQL, and cloud infrastructure, improving prediction reliability. Engineered scalable AI/MLOps architecture integrating LangChain, REST APIs, enterprise databases, and distributed backend services, reducing production latency by 25% and accelerating deployment of new AI capabilities. Built model evaluation frameworks with experimentation, statistical analysis, performance monitoring, and feedback-driven optimization, increasing production model performance by 35%.

GenAI Project Associate at Honeywell

January 1, 2025 - May 1, 2025

Developed enterprise-grade Generative AI applications and intelligent automation leveraging LLMs, vector databases, and scalable cloud-based AI infrastructure. Built and deployed a production GenAI platform using LLMs with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and LlamaIndex, handling 1,000+ requests daily with 98% response accuracy and reducing manual effort by 60%. Designed retrieval and ranking pipelines using semantic search, hybrid retrieval, confidence scoring, and quantitative evaluation metrics to improve relevance, factual grounding, and decision-support quality. Implemented scalable orchestration services using FastAPI/REST and deployment pipelines enabling reliable inference, monitoring, and continuous improvement. Optimized performance via experimentation, prompt engineering, architecture refinement, automated testing, CI/CD, and deployment best practices, improving reliability and reducing operational overhead.

Machine Learning Engineer at SS Infotech

July 1, 2022 - June 1, 2024

Led design, development, and deployment of AI-powered hiring and analytics solutions combining machine learning, LLMs, data engineering, and scalable cloud architectures. Developed CV Robo, an AI-powered recruitment platform leveraging machine learning models, LLMs, SQL databases, FastAPI services, and cloud deployment, improving candidate screening efficiency and accelerating hiring workflows. Architected end-to-end AI applications including data pipelines, feature engineering, model integration, REST APIs, backend services, deployment infrastructure, and enterprise software systems from prototype to production. Built evaluation and monitoring frameworks to measure model performance (latency, ranking accuracy, reliability) and business metrics, supporting continuous optimization.