Sidney Wijngaarde
Software Engineer at Clay
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolSidney Wijngaarde is a full-stack software engineer with 11 years of experience building cloud-native and distributed systems using JavaScript and Go. He has shipped production tooling for Kubernetes management at IBM and contributed backend and MLOps expertise to the Determined AI platform, extending checkpoint metadata APIs and integrating with TensorBoard and TensorFlow. Comfortable across frontend, CLI and microservice stacks, he combines React/Redux/GraphQL work with Go-based service design and CI/CD for containerized deployments. An early hire at Determined AI and now at Clay, Sidney pairs hands-on engineering with customer-facing onboarding and solutions work, a sign of strong product and technical empathy. Outside of product work he’s a self-described terminal guru and lifelong tinkerer, recently exploring serverless, GraphQL, and Istio.
11 years of coding experience
8 years of employment as a software developer
Bachelor of Arts (B.A.) Computer Science, Bachelor of Arts (B.A.) Computer Science at Dartmouth College
Portuguese
Github Skills (16)
api-rest10
rest-api10
mlops10
go10
postgresql10
api-design10
restful-api10
distributed-training9
deep-learning9
tensorflow7
data-science7
pytorch7
keras7
hyperparameter-optimization7
kubernetes6
Programming languages (11)
Github contributions (5)
determined-ai/determined
Jun 2020 - Aug 2020
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
Role in this project:
Back-end Developer & MLOps Engineer
Back-end Developer & MLOps EngineerContributions:30 commits, 81 PRs, 49 pushes in 2 months
Contributions summary:Sidney's commits primarily focused on developing and extending the Determined AI platform's checkpoint metadata API. This involved significant back-end work, including modifying database schemas and implementing REST endpoints using PostgreSQL and Go. The changes included adding features for managing and retrieving metadata associated with checkpoints, which is crucial for tracking experiment configurations and model information within the Determined AI platform.
pytorchdata-sciencedeep-learningdistributed-trainingmachine-learning
RcrsvSquid/pitchback-frontend
Dec 2016 - Feb 2017
Contributions:46 PRs, 180 pushes, 56 branches in 2 months
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