Marc Socastro
Chief AI Officer at Wysewalls
Barcelona, Catalonia, Spain
Summary
🤩
Rockstar🎓
Top SchoolMarc Socastro is a Chief AI Officer and seasoned ML leader with a PhD in wireless communications and over a decade delivering production NLP and information-extraction systems across startups and enterprise teams. He combines full-stack data science skills—project management, data engineering, ML engineering and modeling—to turn research into scalable microservices and MLOps pipelines that dramatically cut costs and latency (e.g., 22x throughput / 97% cost reduction on a Globality extraction pipeline). His career spans impact roles at Globality, Eigen, Darktrace and Streetbees, and includes teaching at Cambridge Spark and UOC plus sustained open-source contributions (notably refactoring and testing improvements to hyperopt). Comfortable operating cross-functionally, he has led product-focused teams, run weekly syncs with business stakeholders, and built tooling like globality-black. He’s entrepreneurial and hands-on—having built a language-learning app (used to learn Lithuanian) and recently joining early-stage Epum before taking on his current role at Wysewalls. He brings a rare blend of academic rigor, production-first engineering, and a penchant for tooling and teaching.
9 years of coding experience
13 years of employment as a software developer
Certificate for Youth Activity Coordinator, Certificate for Youth Activity Coordinator at Minyons Escoltes i Guies de CatalunyaUPC Universitat Politècnica de CatalunyaComputer Science, Computer Science at Coursera, Codecademy, Learn Code
Spanish, Catalan, English, Lithuanian
Stackoverflow
449reputation
42kreached
7answers
1question
Github Skills (14)
algorithm10
hyperparameter-optimization10
algorithms10
python10
testing10
pytest8
pytorch6
nvidia6
jupyter-notebook6
jupyterlab6
gpu6
google-colaboratory6
string-concatenation6
fest4
Programming languages (8)
Github contributions (5)
hyperopt/hyperopt
Dec 2019 - Oct 2020
Distributed Asynchronous Hyperparameter Optimization in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:32 reviews, 9 commits, 37 PRs in 10 months
Contributions summary:Marc's contributions primarily focused on improving the `hyperopt` library. Their work included refactoring the code to remove unused parameters and improve code readability, especially within the `tpe.py` module. The user made significant changes to the randint function, allowing for a lower bound. They also made improvements to the test suite.
pythonasynchronoushyperparameteroptimizationmultiprocessing
marctorsoc/marctorsoc.github.io
May 2018 - Jun 2022
Contributions:101 commits, 9 PRs, 133 pushes in 4 years 1 month
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