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AI/ML Engineer with 4+ years of experience building and deploying production-grade machine learning and Generative AI solutions. Strong hands-on expertise in Python, PyTorch, TensorFlow, LLMs, RAG, LangChain, LlamaIndex, and vector databases to improve retrieval quality, automation, and response performance. End-to-end experience across ML development and MLOps, including model evaluation, deployment automation, monitoring, Docker, Kubernetes, CI/CD, and AWS SageMaker. Proven ability to optimize model workflows and deliver measurable business outcomes in Agile environments.…AI/ML Engineer with 4+ years of experience building and deploying production-grade machine learning and Generative AI solutions. Strong hands-on expertise in Python, PyTorch, TensorFlow, LLMs, RAG, LangChain, LlamaIndex, and vector databases to improve retrieval quality, automation, and response performance. End-to-end experience across ML development and MLOps, including model evaluation, deployment automation, monitoring, Docker, Kubernetes, CI/CD, and AWS SageMaker. Proven ability to optimize model workflows and deliver measurable business outcomes in Agile environments.

Swapnil Shah

AI Engineer, Data Scientist, Programmer, +4

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AI/ML Engineer with 4+ years of experience building and deploying production-grade machine learning and Generative AI solutions. Strong hands-on expertise in Python, PyTorch, TensorFlow, LLMs, RAG, LangChain, LlamaIndex, and vector databases to improve retrieval quality, automation, and response performance. End-to-end experience across ML development and MLOps, including model evaluation, deployment automation, monitoring, Docker, Kubernetes, CI/CD, and AWS SageMaker. Proven ability to optimize model workflows and deliver measurable business outcomes in Agile environments.…AI/ML Engineer with 4+ years of experience building and deploying production-grade machine learning and Generative AI solutions. Strong hands-on expertise in Python, PyTorch, TensorFlow, LLMs, RAG, LangChain, LlamaIndex, and vector databases to improve retrieval quality, automation, and response performance. End-to-end experience across ML development and MLOps, including model evaluation, deployment automation, monitoring, Docker, Kubernetes, CI/CD, and AWS SageMaker. Proven ability to optimize model workflows and deliver measurable business outcomes in Agile environments.

Available to hire

AI/ML Engineer with 4+ years of experience building and deploying production-grade machine learning and Generative AI solutions. Strong hands-on expertise in Python, PyTorch, TensorFlow, LLMs, RAG, LangChain, LlamaIndex, and vector databases to improve retrieval quality, automation, and response performance.

End-to-end experience across ML development and MLOps, including model evaluation, deployment automation, monitoring, Docker, Kubernetes, CI/CD, and AWS SageMaker. Proven ability to optimize model workflows and deliver measurable business outcomes in Agile environments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Beginner

Language

English

Advanced

Hindi

Advanced

Gujarati

Advanced

Work Experience

AI/ML Engineer at BNY

January 1, 2024 - Present

Architected Generative AI and RAG systems using LLM integration, LangChain, LlamaIndex, embedding models, and vector databases, improving retrieval relevance by 38% for financial knowledge and research workflows. Engineered agentic AI and chatbot solutions with Python, FastAPI, LangChain, and PostgreSQL to automate repetitive research activities and reduce manual analyst effort by 35%. Deployed scalable AI workloads using AWS SageMaker, Lambda, ECR, EC2, and S3 to standardize deployment processes and reduce environment provisioning and release time by 40%. Implemented production MLOps with MLflow, Docker, Kubernetes, GitHub Actions, CI/CD, and model monitoring, reducing model release cycles by 32%. Optimized LLM/retrieval workflows using prompt engineering, evaluation, A/B testing, and hyperparameter tuning to improve response quality by 30% while maintaining consistent enterprise performance.

AI/ML Engineer at Vivma Software Inc

January 1, 2021 - August 1, 2022

Developed supervised and unsupervised machine learning solutions using Python, Pandas, NumPy, scikit-learn, XGBoost, and LightGBM, improving predictive performance by 26%. Built NLP solutions using BERT, GPT models, spaCy, NLTK with NER, text classification, and topic modeling, reducing manual text-processing by 40% and improving automated document classification accuracy. Designed computer vision pipelines using OpenCV, YOLO, image classification, object detection, OCR, and transfer learning, improving automated image-processing accuracy by 29%. Engineered distributed data processing workflows using Apache Spark, PySpark, Spark MLlib, Kafka, and Dask to reduce processing time by 33% and support larger datasets. Implemented model experimentation and deployment workflows with MLflow, DVC, Docker, Jenkins, GitLab, and CI/CD to reduce deployment effort by 30% and improve reproducibility.