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I am a full-stack and AI/ML engineer with 7+ years of experience building scalable, cloud-native software and deploying state-of-the-art LLM, GenAI, agentic AI, and NLP systems. I collaborate across cross-functional teams to ship microservices, CI/CD pipelines, and real-time data systems using Python, Java, Kubernetes, and Terraform. I enjoy tackling complex problems and delivering high-quality software that improves user experience. I have hands-on experience with RAG architectures, LangChain, Hugging Face, GPT-3.5/4, Google Gemini, and optimizing end-user experiences. I am excited to build end-to-end AI platforms using Python frameworks, deep learning, agentic AI, and robust DevOps for enterprise applications.…I am a full-stack and AI/ML engineer with 7+ years of experience building scalable, cloud-native software and deploying state-of-the-art LLM, GenAI, agentic AI, and NLP systems. I collaborate across cross-functional teams to ship microservices, CI/CD pipelines, and real-time data systems using Python, Java, Kubernetes, and Terraform. I enjoy tackling complex problems and delivering high-quality software that improves user experience. I have hands-on experience with RAG architectures, LangChain, Hugging Face, GPT-3.5/4, Google Gemini, and optimizing end-user experiences. I am excited to build end-to-end AI platforms using Python frameworks, deep learning, agentic AI, and robust DevOps for enterprise applications.

Jerry Yang

AI Engineer, Full Stack Developer, Data Scientist, +5

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I am a full-stack and AI/ML engineer with 7+ years of experience building scalable, cloud-native software and deploying state-of-the-art LLM, GenAI, agentic AI, and NLP systems. I collaborate across cross-functional teams to ship microservices, CI/CD pipelines, and real-time data systems using Python, Java, Kubernetes, and Terraform. I enjoy tackling complex problems and delivering high-quality software that improves user experience. I have hands-on experience with RAG architectures, LangChain, Hugging Face, GPT-3.5/4, Google Gemini, and optimizing end-user experiences. I am excited to build end-to-end AI platforms using Python frameworks, deep learning, agentic AI, and robust DevOps for enterprise applications.…I am a full-stack and AI/ML engineer with 7+ years of experience building scalable, cloud-native software and deploying state-of-the-art LLM, GenAI, agentic AI, and NLP systems. I collaborate across cross-functional teams to ship microservices, CI/CD pipelines, and real-time data systems using Python, Java, Kubernetes, and Terraform. I enjoy tackling complex problems and delivering high-quality software that improves user experience. I have hands-on experience with RAG architectures, LangChain, Hugging Face, GPT-3.5/4, Google Gemini, and optimizing end-user experiences. I am excited to build end-to-end AI platforms using Python frameworks, deep learning, agentic AI, and robust DevOps for enterprise applications.

Available to hire

I am a full-stack and AI/ML engineer with 7+ years of experience building scalable, cloud-native software and deploying state-of-the-art LLM, GenAI, agentic AI, and NLP systems. I collaborate across cross-functional teams to ship microservices, CI/CD pipelines, and real-time data systems using Python, Java, Kubernetes, and Terraform. I enjoy tackling complex problems and delivering high-quality software that improves user experience.

I have hands-on experience with RAG architectures, LangChain, Hugging Face, GPT-3.5/4, Google Gemini, and optimizing end-user experiences. I am excited to build end-to-end AI platforms using Python frameworks, deep learning, agentic AI, and robust DevOps for enterprise applications.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Javanese

Advanced

Afar

Advanced

Work Experience

Backend & AI Developer at Microsoft

January 1, 2022 - March 1, 2026

Designed and implemented the Dreaming Worker pipeline to analyze uploaded user content (audio, PDFs, Markdown, DOCX) and generate structured Insights ('Moments' and 'Dreams') using LLM-powered workflows. Built a multi-tenant content ingestion system with SeaweedFS, NATS JetStream, and PostgreSQL/TiDB to manage asynchronous AI processing across tenant-specific workflows. Developed file upload and moment-creation APIs with FastAPI, integrating AI workflow components for automated insight extraction. Implemented CLI orchestration for per-tenant and batch analysis, including model selection, lookback windows, and email digest generation. Created automated HTML email summaries and retrieval pipelines for chunking, embeddings, and multi-format content search. Built LLM-powered and agentic workflow components interfacing with OpenAI, Claude, and Gemini APIs for processing, context retrieval, and structured generation. Integrated embeddings and vector indexes to support semantic search. Implem

Backend & AI Engineer at Microsoft

January 1, 2022 - Present

Designed and implemented the Dreaming Worker pipeline to analyze uploaded user content (audio, PDFs, Markdown, DOCX) and generate structured Moments and Dreams via GPT-4-class LLMs. Built a multi-tenant content ingestion system with SeaweedFS (S3-compatible), NATS JetStream, and PostgreSQL/TiDB to manage large-scale asynchronous processing. Developed file upload and moment creation APIs using FastAPI (Python) integrating LLM agents for automated insight extraction. Implemented CLI orchestration commands to run per-tenant or batch analysis, including model selection, lookback windows, and email digest generation. Created automated email reporting via templated HTML summaries of generated moments using SMTP server. Developed RAG-style pipelines for chunking, embedding, and retrieval of multi-format content (PDF, DOCX, Markdown, audio). Developed agentic AI systems that interface with OpenAI, Anthropic, and Claude APIs to process user content and generate structured insights. Integrated O

Backend & AI Developer at Silicon Labs

July 1, 2020 - January 1, 2022

Collaborated with cross-functional teams to support financial analysis, NLP-assisted decision-support, and internal knowledge workflows. Implemented backtesting workflows and NLP-based assistant features for user education and research. Contributed to a legal/financial document Q&A system with NLP, search, retrieval, summarization, and structured responses. Designed backend pipelines for document ingestion, indexing, search, and Q&A across legal/financial sources. Built API integrations for user-facing applications with document processing, retrieval, and analytics. Created dashboards for financial data reporting and scaled backend systems to support 20,000 daily active users via FastAPI and Node.js, improving latency and throughput through refactoring and caching. Deployed data and ML workflows on Azure and Google Cloud (Kubeflow, BigQuery). Mentored junior engineers and contributed to best practices for scalable distributed systems, including a crypto arbitrage bot for real-time deci

Backend & AI Engineer at Silicon Labs

July 1, 2020 - January 1, 2022

Led cross-functional teams leveraging ML, GenAI, and NLP for financial data analysis and AI-powered investment insights. Implemented backtesting and a generative AI chat assistant for user education and informed decision-making. Led the development of a legal chatbot powered by LLMs, enhanced with agentic AI technology, and deployed on GCP using Kubeflow and BigQuery. Demonstrated expertise in cloud-based NLP solutions. Created interactive dashboards for financial data communication using Tableau. Implemented cutting-edge research in generative AI (LangChain, ChatGPT, Ollama.ai). Scaled distributed backend systems supporting 20,000 daily active users using FastAPI and Node.js, improving request latency and throughput via API refactoring, advanced caching strategies, and database query optimization (MySQL, RocksDB). Built and maintained enterprise-grade microservices in Python and Django for low-latency, high-availability systems. Built and maintained responsive dashboards and client po

Software Developer at Samsung Electronics

June 1, 2019 - August 31, 2019

Supported ETL pipelines and ML engineering for research analytics and document indexing. Worked on ML/NLP tasks using BERT, transformers, graph attention networks, and LSTM; streamlined data analytics and workflow automation with Alteryx. Designed workflows for multi-source data ingestion, transformation, and indexing, and built RESTful backend services for internal data access and automation. Contributed to cloud deployments and front-end prototyping for search and analytics interfaces.

Machine Learning Engineer at Samsung Electronics

June 1, 2019 - August 1, 2019

Provided services for an officer in creating data pipelines and ML engineering. Worked on machine learning, NLP, AWS, Elasticsearch/OpenSearch and helped create ETL for Global Hydrogen Index with Elasticsearch. Utilized BERT for NLP-based deep learning in voice recognition and integrated agentic AI with graph attention networks, transformers, and LSTM architectures. Streamlined data analytics and workflow automation using Alteryx. Designed and implemented complex workflows integrating data from various sources, transforming and cleaning data, and generating actionable insights. Participated in the design, development, and deployment of scalable backend services and distributed systems supporting high-traffic e-commerce and financial platforms. Built and maintained RESTful APIs and microservices using Python for millions of daily users. Combined DNNs with SVM, KNN, and tree models using grid search, increasing performance by 15%. Architected and optimized cloud infrastructure on AWS wit

Software Developer at AMD

January 1, 2019 - April 30, 2019

Supported ML workflows in distributed containerized environments using TensorFlow, Keras, and scikit-learn. Built generative models for anomaly detection and used R for statistical analysis and visualization. Automated data processing with Alteryx, and developed ML/automation pipelines that reduced manual tasks. Delivered backend services and RESTful APIs, and contributed to cloud infrastructure using AWS.

Full Stack Engineer at AMD

January 1, 2019 - April 1, 2019

Implemented machine learning in a distributed containerized fashion using TensorFlow, Keras, Azure Docker containers, and scikit-learn within an Agile methodology. Built generative adversarial models for anomaly detection and utilized R for statistical analysis and data visualization. Designed and implemented complex workflows integrating data from various sources, transforming and cleaning data, and generating actionable insights. Built and maintained RESTful APIs and microservices using Python and Node.js, integrating with SQL Server and Azure-based services. Implemented CI/CD pipelines with GitHub Actions and AWS CodePipeline. Integrated AI/ML features using OpenAI APIs and Hugging Face models. Monitored and improved application reliability using Prometheus, Grafana, and CloudWatch.

Software Developer at Hewlett Packard Enterprise

June 1, 2018 - August 31, 2018

Supported scalable backend services in Java and Python, integrating with VMware virtualization APIs. Developed and enhanced RESTful and gRPC APIs for automation and orchestration. Wrote scripts to automate ETL and data collection, and supported data pipelines with SQL/NoSQL databases. Optimized distributed system reliability, scalability, and maintainability, collaborating across teams in an Agile environment.

Backend Engineer at Hewlett Packard Enterprise

June 1, 2018 - August 1, 2018

Built and maintained scalable backend services in Java and Python, integrating with VMware’s virtualization stack and APIs (vSphere, ESXi, vCenter). Developed and enhanced RESTful and gRPC APIs to support automation, orchestration, and third-party integrations. Wrote scripts in Python and Bash to automate data collection, parsing, and storage. Supported integration of backend data pipelines with MySQL and NoSQL databases for large-scale data indexing. Optimized scripts to automate ETL processes. Collaborated with senior engineers to improve system reliability and scalability for production workloads.