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Vetted AI Engineers in the Greater Seattle

Pre-screened and vetted in the Greater Seattle.

AWSAmazon EC2Amazon S3Apache AirflowAWS LambdaA/B Testing
AB

Atush Bhalla

Mid-level Gameplay/AI Engineer specializing in Unity, XR, and narrative NPC systems

Seattle, WA2y exp
SupercellUSC
A/B TestingAIAlgorithmsAnalysis of AlgorithmsAPI DevelopmentAsynchronous Programming+51
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BR

Bhavinkumar Rathava

Mid-level AI/Software Engineer specializing in NLP pipelines and LLM-driven automation

Bellevue, WA3y exp
Kaizen AnalytixNorthwestern University
AgileAmazon Web Services (AWS)Anomaly DetectionAPI DesignAutoencodersAWS CloudFormation+50
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PT

Pranav Thorat

Mid-level Machine Learning Engineer specializing in MLOps and applied AI

Seattle, WA5y exp
Hextropian Systems Inc.NYU
AirflowAmazon EC2Amazon ECSAmazon Web Services (AWS)AndroidAngular+122
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JJ

Jessica James

Junior AI/Data Engineer specializing in LLM agents and data governance automation

Seattle, WA2y exp
Chicory AINortheastern University
Adaptive RAGAgent APIAI agentsAirflowApache AirflowAWS+96
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SG

Shweta Gupta

Screened

Senior Backend Software Engineer specializing in Java microservices, Kafka, and AWS

Seattle, WA6y exp
EasyBee AIUC Irvine

AI engineer who shipped a production chat assistant for a storage company by building the underlying RAG-style knowledge base (document ingestion, chunking/embeddings, FAISS vector store) and an admin update interface to keep content current. Also has full-stack delivery experience (Python REST APIs + React/TypeScript UI) and AWS operations using Terraform/Jenkins, including handling a real production performance incident by optimizing DB queries and adding auto-scaling.

A/B TestingAgileAirflowAPI TestingAWSAWS DynamoDB+111
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DP

Deep Patel

Screened

Junior AI/ML Engineer specializing in NLP, LLMs, and MLOps deployment

Seattle, WA1y exp
Firenix Technologies Pvt. Ltd.University of Oklahoma

Built and deployed NeuroDoc, a production-grade RAG system for PDF Q&A that delivers citation-backed answers with strong anti-hallucination guardrails. Experienced in orchestrating and scaling ML/LLM pipelines with Kubernetes, Airflow/Prefect, and PyTorch Distributed, and in building rigorous evaluation and citation-verification tooling to ensure reliability in production.

AI/ML EngineeringMachine LearningDeep LearningSupervised LearningUnsupervised LearningRegression+98
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