Tim gretler
DeFi Trading Engineer at GSR
Zurich, Zurich, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolTim gretler is a DeFi Trading Engineer based in Zurich with seven years of experience building production-grade distributed systems, blockchain clients, and infrastructure automation. He has strong hands-on experience across networking and P2P systems from two roles at DFINITY and practical DevOps work—contributing to Cortex’s ML deployment tooling and implementing rolling updates, GPU support, and API Gateway integrations. On the protocol side he’s contributed to high-profile open-source projects such as Lighthouse (an Ethereum consensus client) and the Internet Computer, improving sync/validation, block proposing, and low-level scheduler and ledger components. Comfortable across Rust and systems-level code as well as Terraform/Ansible-driven automation, he brings a blend of trading-facing engineering and deep protocol expertise to production environments. Notably, his background combines ETH Zürich training with cross-cutting experience in both consensus clients and ML deployment infrastructure, enabling him to bridge low-level protocol work and large-scale operational concerns.
7 years of coding experience
3 years of employment as a software developer
Master's degree Information Technology, Master's degree Information Technology at ETH Zürich
Github Skills (30)
kubernetes10
docker10
dockers10
infrastructure10
staking10
aws10
etherum10
api-gateway10
ethereum10
cryptography10
blockchain10
kubernetes-pods10
rust10
concurrency10
architecture9
Programming languages (13)
Github contributions (5)
dfinity/ic
Jan 2022 - Jan 2023
Internet Computer blockchain source: the client/replica software run by nodes
Role in this project:
Back-end Developer
Back-end DeveloperContributions:95 reviews, 293 commits, 29 PRs in 1 year
Contributions summary:Tim's contributions focused on the Internet Computer (IC) blockchain source code, with changes primarily related to low-level system components. Their work included integrating and improving internal systems and managing components such as the scheduler, data structures for the blocks and ledger, and metrics to measure the adapter's activity. The user also worked on the canister http adapter by setting up the server with a mock client to test https requests.
replicablockchainnodesdfinityinternet
cortexlabs/cortex
Apr 2020 - Aug 2020
Production infrastructure for machine learning at scale
Role in this project:DevOps Engineer
DevOps EngineerContributions:10 commits, 16 PRs, 68 pushes in 4 months
Contributions summary:Tim's commits primarily focus on infrastructure and deployment-related tasks for machine learning applications. The user implemented rolling updates for a DaemonSet, configured logging and metrics, and added support for GPU configurations. They also worked on API Gateway integration, including creating and managing API gateway routes, integrations and VPC links. Furthermore, the user improved the deployment process by adding a wait condition for the API Gateway VPC Link and setting tags on log groups.
infrastructuremachine-learningscaleproductionat-scale
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