# Steven Liu

> Software Engineer @ Amazon

Location: San Francisco, California, United States
Profile: https://flows.cv/stevenliu

Hi! I am a software engineer with experience in backend services, fullstack web applications, and machine learning solutions. I have worked on developing deep learning training framework, productizing and deploying large-scale foundation models, building automated ETL pipelines, and managing ML platform infrastructure using infrastructure-as-code. With a strong background in distributed computing, cloud technologies and web development, I work closely with engineering and research teams to develop scalable, high-impact solutions.

I am passionate about building large-scale software systems, driving data-driven insights, and solving complex technical challenges that create meaningful impact.

📩 Happy to connect and you may reach out at jiawen.steven.liu@gmail.com

Technical Skills
🔹 Machine Learning & AI: Python, PyTorch, PyTorch Lightning, Distributed Computing, MLFlow, CI/CD, Docker, Streamlit, Unit & Integration Testing

🔹 Full-Stack Development: TypeScript, HTML, CSS, React, Vite, Node.js, Express.js, D3.js

🔹 Cloud & Infrastructure: AWS (API Gateway, Batch, Bedrock, CDK, CloudFormation, CloudWatch, DynamoDB, ECR, EC2, ECS, IAM, Lambda, MWAA/Airflow, S3, SageMaker, SNS, Step Functions), Databricks, Google Cloud

🔹 Data Science & Analytics: Python, R, SQL, Tableau, Databricks, PySpark

🔹 Project Management: MS Project, Lean Six Sigma, Jira, Agile Methodology

## Work Experience
### Software Engineer II - Stores Foundational AI @ Amazon
Jan 2022 – Present | San Francisco Bay Area
Productionize large-scaled foundational models through SDK and ML portable library with PyTorch and PyTorch Lightning framework for model training, async S3 checkpointing , and embedding generation. 

Build product search fullstack website with React, TypeScript, Tailwind CSS along with RESTful API Gateway connecting with various backend services. Automate creation and hosting multiple large-scaled foundation models & LLMs through deploying them to SageMaker endpoints performing real-time inference solutions and KNN retrieval through OpenSearch clusters. Build online LLM chatbots, offline batch inference, and fine-tuning services using AWS Bedrock, Batch, and Step Function.

Manage deep learning compute platform and training infrastructure with AWS Batch and EC2. Build backend ML data pipelines, CI/CD, release management, and distributed deep learning framework with end-to-end support for multiple engineering and science teams across Amazon.

### Instructional Associate - Machine Learning @ Georgia Institute of Technology
Jan 2022 – Jan 2026
ISYE 7406 (Prof. Yajun Mei) and MSA 6748 (Dr. Joel Sokol) - Instruct analytics and ML lessons to 400+ students in MOOC. Develop onboarding guide and catalog project to streamline process and collect data.

### Data Systems Engineer - Commercial Engines @ Pratt & Whitney
Jan 2017 – Jan 2022 | Greater Hartford
Developed predictive analytical models for engine component failures to improve business metrics.
Designed High Pressure Compressor (HPC) rotors and cases for commercial and military engines.

### Teaching Assistant - Mechanical Engineering @ Cornell University
Jan 2016 – Jan 2017 | Ithaca, New York Area
MAE 2250 Mechanical Synthesis & MAE 3240 Heat Transfer (Prof. Michel Louge)
Led lab discussions, graded assignments, and taught mill, lathe, and CAD for 75 students.

### Research Assistant - Space Systems Design Studio @ NASA - National Aeronautics and Space Administration
Jan 2015 – Jan 2017 | Ithaca, New York Area
On-Orbit Autonomous Assembly of Nanosatellites (OAAN) research with NASA Langley Research Center.
Flux-Pinning Orbiting Sample for Mars (FPOS) research with NASA Jet Propulsion Laboratory.

### Mechanical Engineering Intern @ NYC HR Division of Architecture and Engineering - Bureau Space and Design
Jan 2014 – Jan 2014 | New York, New York, United States
Develop and manage HVAC, pipework, plumbing and construction blueprints for architectural buildings.

### Astrophysics Research Intern @ American Museum of Natural History
Jan 2012 – Jan 2013 | New York, New York, United States
• Applied scientific methods to explore the relationship between vortices and planetary formation
• Compiled collected data of vorticities and kinetic energy of vortices
• Created computer simulation of vortex formations over time with sorted data
• Extrapolated parameters for the vortices from analysis of the data sets
• Co-authored on a paper called, "The Effect of Subcritical Baroclinic Instability on Kinetic Energy of Vortices in Protoplanetary Disks"

### Electrical Engineering Intern @ The Cooper Union
Jan 2012 – Jan 2012 | New York, New York, United States
• Developed and pre-assembled the sumorobot in Solidworks
• Programmed the robot in C for it to perform specific tasks
• Constructed the robot with laser-cutted pieces


## Education
### Master of Science - MS in Analytics
Georgia Institute of Technology

### Bachelor of Science - BS in Mechanical Engineering
Cornell University

### High School
New Explorations Into Science, Technology + Math (NEST+m)


## Contact & Social
- LinkedIn: https://linkedin.com/in/jia-wen-steven-liu

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Source: https://flows.cv/stevenliu
JSON Resume: https://flows.cv/stevenliu/resume.json
Last updated: 2026-03-22