Ata Mahjoubfar
Director Of Machine Learning at Target
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolAta Mahjoubfar is a Director of Machine Learning based in Sunnyvale with 11 years of experience building production-ready deep learning and computer vision systems. At Target he leads multimodal auto-labeling, on-shelf object detection, AI accelerators, private-cloud supercomputing for distributed training, and an MLOps platform that moves models from containerized training to deployment. His background spans industry and academia—from low-latency cell detection and label-free cancer diagnostics during a CNSI postdoc to a Ph.D. at UCLA where he developed the world’s fastest surface inspector—giving him rare expertise in both high-throughput systems and sensitive scientific imaging. He combines research-grade rigor with practical delivery, frequently translating advanced models into scalable pipelines and hardware-aware solutions for retail and enterprise use.
11 years of coding experience
11 years of employment as a software developer
Master of Science (M.Sc.) Electrical Engineering, Master of Science (M.Sc.) Electrical Engineering at University of TehranUniversity of California, Los Angeles
Github Skills (57)
unity3d10
notebook10
python10
jupyter10
machine-learning10
deep-learning10
tensorflow10
neural-network10
deep-reinforcement-learning10
minikube10
serve10
data-science9
docker-image9
reinforcement-learning9
google-kubernetes-engine9
Programming languages (9)
Github contributions (5)
atamahjoubfar/docker-quickstart-cheatsheet
May 2016 - Jan 2022
A quick-start cheatsheet for docker containers
Contributions:16 commits, 1 PR, 14 pushes in 5 years 9 months
containersseccompdocker-machinepodmandocker
atamahjoubfar/My-UCLA-Dissertation
Nov 2014 - Jun 2015
Contributions:18 commits in 6 months
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