Simone Primarosa is a machine-learning-focused software engineer with 11 years of experience building scalable systems across startups and large tech companies, currently a founding member of the technical staff at Boltz after several senior engineering roles at Google. He has deep expertise in search ranking, distributed data processing (contributions to Apache Beam’s Go SDK), and practical ML tooling (improvements to the widely used Hugging Face transformers examples). A First Class BSc from Sapienza and an MPhil in Advanced Computer Science from Cambridge underline a strong research foundation that complements hands-on product delivery—from launching features in Google Maps to architecting Busrapido’s platform that served tens of thousands of users. Comfortable across languages and stacks (Go, Java, JavaScript, PyTorch), he combines production-grade engineering with a researcher's attention to model and system correctness. Less obvious: he has repeatedly bridged research and production, fixing bugs in major embedding frameworks and shipping instrumentation and logging improvements that make ML experiments and pipelines more reliable.
11 years of coding experience
10 years of employment as a software developer
Master of Philosophy - MPhil, Advanced Computer Science, Master of Philosophy - MPhil, Advanced Computer Science at University of Cambridge
Bachelor of Science - BSc, Computer Science, Bachelor of Science - BSc, Computer Science at Sapienza Università di Roma
High School Diploma, Electrical and Electronics Engineering, High School Diploma, Electrical and Electronics Engineering at IIS Evangelista Torricelli
Apache Beam is a unified programming model for Batch and Streaming data processing.
Role in this project:
Back-end Developer
Contributions:9 commits, 7 PRs, 14 comments in 2 months
Contributions summary:Simone primarily contributed to the Go SDK of the Apache Beam project, focusing on enhancements to the `CreateList` function. Their work involved refactoring the function, improving test coverage, and fixing a bug related to count operations on empty PCollections. The user also updated docstrings to improve clarity and maintainability. These changes demonstrate a focus on improving the core functionality and robustness of the Beam SDK.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Role in this project:
ML Engineer
Contributions:5 commits, 4 PRs, 8 comments in 4 months
Contributions summary:Simone primarily focused on improving logging messages and adding support for new models within the GLUE example. Their commits involved modifying existing code to enhance informational output during processing steps and extending the functionality of the example script to accommodate Albert and XLMRoberta models. They also addressed a bug related to caching behavior in PyTorch Lightning examples.
pythonbertspeech-recognitionstate-of-the-artflax
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Simone Primarosa - Founding Member Of The Technical Staff at Boltz