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AI/ML engineer with 9 years of experience implementing and developing AI/ML software systems using Python and FastAPI. Experienced integrating local implementations and online APIs for service orchestration, building agentic pipelines, and deploying containerized AI services. Proficient in monitoring AI workflows, implementing CI/CD, and modeling development and evaluation. Hands-on experience with LLM-based reasoning/agents, RAG systems, speech pipelines, distributed training (FSDP/DDP), and building end-to-end hybrid systems for privacy-preserving Q&A and retrieval.…AI/ML engineer with 9 years of experience implementing and developing AI/ML software systems using Python and FastAPI. Experienced integrating local implementations and online APIs for service orchestration, building agentic pipelines, and deploying containerized AI services. Proficient in monitoring AI workflows, implementing CI/CD, and modeling development and evaluation. Hands-on experience with LLM-based reasoning/agents, RAG systems, speech pipelines, distributed training (FSDP/DDP), and building end-to-end hybrid systems for privacy-preserving Q&A and retrieval.

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AI Engineer, Software Engineer, Back-End Developer, +3

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AI/ML engineer with 9 years of experience implementing and developing AI/ML software systems using Python and FastAPI. Experienced integrating local implementations and online APIs for service orchestration, building agentic pipelines, and deploying containerized AI services. Proficient in monitoring AI workflows, implementing CI/CD, and modeling development and evaluation. Hands-on experience with LLM-based reasoning/agents, RAG systems, speech pipelines, distributed training (FSDP/DDP), and building end-to-end hybrid systems for privacy-preserving Q&A and retrieval.…AI/ML engineer with 9 years of experience implementing and developing AI/ML software systems using Python and FastAPI. Experienced integrating local implementations and online APIs for service orchestration, building agentic pipelines, and deploying containerized AI services. Proficient in monitoring AI workflows, implementing CI/CD, and modeling development and evaluation. Hands-on experience with LLM-based reasoning/agents, RAG systems, speech pipelines, distributed training (FSDP/DDP), and building end-to-end hybrid systems for privacy-preserving Q&A and retrieval.

Available to hire

AI/ML engineer with 9 years of experience implementing and developing AI/ML software systems using Python and FastAPI. Experienced integrating local implementations and online APIs for service orchestration, building agentic pipelines, and deploying containerized AI services.

Proficient in monitoring AI workflows, implementing CI/CD, and modeling development and evaluation. Hands-on experience with LLM-based reasoning/agents, RAG systems, speech pipelines, distributed training (FSDP/DDP), and building end-to-end hybrid systems for privacy-preserving Q&A and retrieval.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

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Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

Work Experience

Senior AI Engineer at Booz Allen Hamilton

March 1, 2024 - March 1, 2026

Led architecture and development of an LLM reasoning agent using OpenAI o4-mini and GPT-5.4, leveraging the React framework to deliver automated insights and decision-making for cryptocurrency and NFT investments. Directed integration of complex function-calling pipelines enabling autonomous execution of technical analysis, sentiment/news evaluation, and market filtering across diversified digital assets. Spearheaded design and implementation of a custom Python-based backtesting engine (leveraging Backtrader) to benchmark and analyze the efficacy of LLM-driven market forecasts. Provided accurate context-forecast synthetic datasets and fine-tuned 30B class LLMs for market prediction using temporal patterns and extreme points.

Senior AI Engineer at Ginger

January 1, 2023 - December 1, 2023

Worked on RAG-enhanced speech to speech pipelines. Developed local and API-based speech pipelines using Whisper, HF Transformers, and OpenAI real-time APIs. Implemented JIT compilation for a local STT model using native PyTorch, reducing latency by 40%. Integrated with VoIP using Asterisk and used agentic workflows to route user queries to sub-tasks and answer based on RAG. Built an end-to-end Hybrid RAG system to enhance a local Q&A LLM for answering queries based on internal documents while preserving anonymity and privacy. Trained a text embedding model for document retrieval on top of XLM-RoBERTa-Large on distributed GPUs using contrastive learning (InfoNCE) and DeepSpeed-accelerated stack; improved internal document retrieval precision from 70% to 95%.

AI Software Developer at AI Software Developer (company name not specified)

September 1, 2021 - September 1, 2022

Deployed Ethereum smart contract generation using LLMs with ~89% success rate for generating coherent contracts. Deployed Ethereum smart contract mutation testing using React architecture and a chain-of-prompting pipeline, reaching +95% success rate for finding mutation candidates. Scaled smart contract pipelines to thousands of users using advanced sync caching strategies with TTL and LRU caching.

AI Software Developer at Inworld AI

September 1, 2021 - September 1, 2022

Deployed Ethereum smart contract generation using LLMs with 89% success rate for generating coherent contracts. Deployed Ethereum smart contract mutation testing using a React architecture and Chain of Prompting pipeline, reaching +95% success rate in finding mutants. Scaled smart contract pipelines to thousands of users using advanced sync architectures using TTL and LRU caching strategies.

Machine Learning Engineer at Scale AI

December 1, 2018 - August 1, 2021

Developed a recommender system based on collaborative filtering and upgraded it to deep recommender systems for better semantic recommendations. Implemented the recommender pipeline using FastAPI for endpoints and SQLite for handling user information; used Docker for containerization. Scaled the project to handle 120k users with 8k concurrent users.

Software Engineer at PCC A (Part Time)

July 1, 2016 - June 1, 2018

Worked on backend systems scaling personalized medicine assistants using microservices and enhanced Java design patterns. Deployed databases using both relational and non-relational databases using a custom infrastructured design. Implemented aggressive caching strategies to reduce the system's workload on peak periods using LRU caching methods.