Tarmily Wen
@tarmilywen
I build production AI systems spanning computer vision, generative AI, RAG, and scalable MLOps platforms.
What I'm looking for
I've built production AI systems at Walmart, Everon, ADT, and Percepta, spanning computer vision, video analytics, predictive modeling, generative AI, and enterprise automation.
At Walmart, I lead machine learning engineering for supply-chain and warehouse automation, delivering distributed data pipelines, real-time computer-vision inference, model serving, observability, and cloud-native deployment. Previously at Everon and ADT, I led AI/ML teams and built RAG, vector search, LLM evaluation, predictive analytics, and MLOps platforms that reduced model deployment cycles from three months to two weeks and reduced unsupported AI-generated responses by 40%.
My work turns research into reliable products using Python, PyTorch, TensorFlow, Spark, Kubernetes, AWS, GCP, and Azure. I also mentor engineers in computer vision, ML system design, dataset management, MLOps, and production deployment.
Experience
Work history, roles, and key accomplishments
Led end-to-end machine learning engineering lifecycle for large-scale computer vision systems in supply chain and warehouse automation. Designed distributed ML pipelines and production systems using Python, PyTorch, TensorFlow, Spark, and Kubernetes.
Team Lead – Machine Learning Researcher
Everon
Oct 2023 - Jan 2025 (1 year 3 months)
Led development of scalable video monitoring platforms and computer vision pipelines for enterprise security. Implemented RAG and LLM evaluation frameworks, reducing unsupported AI responses by 40%.
Led end-to-end research and productionization of enterprise ML solutions, including predictive analytics and MLOps platform on GCP. Reduced model deployment cycles from 3 months to 2 weeks.
Computer Vision Engineer / Researcher
Percepta
May 2019 - Jul 2021 (2 years 2 months)
Designed end-to-end ML systems for real-time retail video analytics, including data pipelines and deep learning models. Reduced manual data preparation effort by 50% and training iteration cycles by 30%.
Conducted research on computer vision and perception projects, developing and evaluating deep learning models for object affordance detection and image synthesis.
Education
Degrees, certifications, and relevant coursework
University of Pennsylvania
Doctor of Philosophy, Computer Science
2020 -
Pursuing a Doctor of Philosophy in Computer Science at the University of Pennsylvania.
University of Pennsylvania
Bachelor of Science, Physics and Mathematics
2014 - 2019
Earned a Bachelor of Science in Physics and Mathematics from the University of Pennsylvania.
University of Pennsylvania
Master of Science, Computer Science
2014 - 2019
Earned a Master of Science in Computer Science from the University of Pennsylvania.
Tech stack
Software and tools used professionally
AWS Glue
Google Cloud Platform
GitHub
Kubernetes
Jenkins
GitHub Actions
React Native
Jupyter
NumPy
Pandas
PySpark
MySQL
PostgreSQL
MongoDB
Node.js
Django
Spring Boot
Next.js
Material-UI
three.js
Databricks
Figma
OpenCV
FFMPEG
Redis
Terraform
Azure DevOps
Jira
WebGL
JavaScript
Java
ES6
MATLAB
TensorFlow
PyTorch
MLflow
scikit-learn
Keras
Kubeflow
Kafka
MQTT
FastAPI
Grafana
Prometheus
Linux
GraphQL
Elasticsearch
OpenSearch
Milvus
Serverless
Azure Functions
Airflow
s3-lambda
CUDA
SQL
XGBoost
SciPy
Hugging Face
LightGBM
Temporal
LangChain
LlamaIndex
Weaviate
Pinecone
Ray
LanceDB
vLLM
Cursor
NVIDIA Triton Inference Server
Great Expectations
ArgoCD
Synthesized
GitHub Copilot
Ragas
Bash
Scale AI
Agentic
Faiss
Microsoft Fabric
Loops
SGLang
Factory
Availability
Location
Authorized to work in
Social media
Job categories
Skills
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