Joan Martínez
Principal Engineer at Redis
Barcelona, Catalonia, Spain
Summary
🤩
Rockstar🎓
Top SchoolJoan Martínez is a Principal Engineer based in Barcelona with 9 years of experience building production-grade systems in C/C++ and Python, and strong expertise across ML/AI, cloud-native serving, and big data. He has led engineering and architecture for embedding-based inference and serving platforms at Jina AI and now drives technical initiatives at Redis, mentoring teams and making key design decisions. His open-source contributions include improving LightGBM integration in Microsoft's SynapseML and enhancing vectorization and embedding modules in Weaviate and Jina, reflecting deep practical work on vector search and scalable ML pipelines. Earlier roles span search-ranking engineering, columnar DB optimizations, and robotics research—giving him a rare blend of low-level systems performance skill and applied ML know-how. Joan’s background in robotics and a Master in Computer Vision inform his pragmatic approach to ML model serving, where robustness against edge cases (e.g., cosine distance with zero vectors) and production stability are priorities. He combines systems-level thinking with hands-on contributions to prominent OSS projects, making him effective at shipping reliable, high-performance ML infrastructure.
8 years of coding experience
10 years of employment as a software developer
Master in Computer Vision Master in Computer Vision, Master in Computer Vision Master in Computer Vision at Universitat Autònoma de BarcelonaUPC Universitat Politècnica de Catalunya
Spanish, Catalan, English, German, French
Stackoverflow
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Github Skills (48)
continuous-deployment10
unit-testing10
apache-spark10
debug10
integrate10
python10
apidoc10
data-science10
machine-learning10
pyspark10
vector-database10
application-integration10
indexing10
integrations10
data-structure10
Programming languages (14)
Github contributions (5)
jina-ai/examples
Jul 2020 - Apr 2021
Jina examples and demos to help you get started
Role in this project:
ML Engineer
ML EngineerContributions:399 reviews, 175 commits, 142 PRs in 10 months
Contributions summary:Joan contributed significantly to the example projects, primarily focusing on integrating and utilizing machine learning techniques within the Jina AI ecosystem. Their commits demonstrate the implementation of indexing and searching functionalities using various vector search methods such as Faiss, Annoy, and NumPy. The user added evaluation metrics for assessing search performance and worked on adapting the examples to newer Jina AI versions.
nlppythononboardingget-starteddeep-learning
jina-ai/serve
May 2020 - Jan 2023
☁️ Build multimodal AI applications with cloud-native stack
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:4981 reviews, 1354 commits, 3239 PRs in 2 years 8 months
Contributions summary:Joan's contributions focused on implementing unit tests and addressing problems related to the cosine distance function. They added test cases to address issues related to the behavior of the cosine distance metric with zero-valued vectors, indicating a focus on improving model robustness and correctness. Their work involved modifying code to refine the indexing process and ensure accurate retrieval.
opentelemetryllm-inferencecreative-aigrpcproduction
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