Can Karakus
Member Of Technical Staff at Anthropic
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolCan Karakus is a machine learning and distributed systems engineer with seven years of experience building scalable training infrastructure and applied ML products in the San Francisco Bay Area. He has held research and production roles from academia to industry, culminating in applied-science and Member of Technical Staff positions at AWS, Contextual AI, and Anthropic. At AWS he architected and shipped model-parallel training libraries for SageMaker and led large-scale distributed training efforts; his PhD work at UCLA produced practical redundancy and straggler-mitigation techniques that doubled training speed in cluster settings. He combines rigorous theoretical background in electrical engineering with hands-on systems implementation across MPI, EC2, and production ML services. Colleagues would note his knack for turning research ideas into robust, deployable tooling that improves throughput and fault tolerance in real workloads. Based in the Bay Area, he brings a blend of academic depth and production engineering focus to large-model and distributed ML challenges.
7 years of coding experience
14 years of employment as a software developer
High School, High School at İzmir Fen LisesiBS Electrical&Electronics Engineering, BS Electrical&Electronics Engineering at Bilkent UniversityUniversity of California, Los Angeles
Github Skills (57)
keras-tensorflow10
pytorch10
deploying10
python10
jupyter10
machine-learning-models10
mpi10
machine-learning10
mxnet10
inference10
reinforcement-learning10
sagemaker10
keras10
amazon-sagemaker10
huggingface10
Programming languages (3)
Github contributions (5)
karakusc/training_results_v0.7
Dec 2020 - Jan 2021
Training v0.7 results
Contributions:5 reviews, 3 PRs, 11 pushes in 1 month
training
karakusc/xla
Jun 2024 - Jun 2024
Enabling PyTorch on XLA Devices (e.g. Google TPU)
Contributions:5 pushes, 3 branches in 5 days
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