João Neves

📇 Contacts

LinkedIn | X/Twitter | Github | Website | Email

👨‍💻 Professional Experience

Advanced Software Engineer @ Feedzai, Lisbon (February 2024-Present)

Conduct cutting-edge research in computer systems, including operating systems, distributed systems, and networked systems.

• Design and develop company-wide Machine Learning systems
• Collaborate with cross-functional teams to integrate research findings into practical applications and products.
• Publish research findings in top-tier conferences and journals.
• Stay updated with the latest advancements in systems research and incorporate relevant technologies into ongoing projects.
• Technologies used: Docker, Kubernetes, Kafka, Quarkus, Flux, Java

Senior ML Engineer @ Farfetch, Lisbon (June 2022-February 2024)

Design and implement recommendation systems to improve the User experience in the Marketplace

• Successfully collaborated on developing a virtual assistant by leveraging LLMs for prompt engineering and effectively deploying it as an API.
• Proficiently contributed to implementing and optimising a Vector Search Engine (Vespa) to enhance recommendation systems.
• Design and implement recommendation systems to improve the User Experience
• Produce resilient, high-available and scalable systems to host ML models (e.g., APIs).
• Support ML development by implementing Data Engineering systems
• Technologies used: Large Language Models (LLM), MLflow, PySpark, Pandas (Software), Kafka, Kubernetes, Azure Databricks, Airflow, Python, Flask

Lead Tech Engineer & ML Engineer @ Siemens, Lisbon (January 2019-June 2022)

Design and implement detection and analytics cloud-based ML systems for CyberSecurity

• In-house MLOps framework development
• Automation frameworks for clients
• Phishing analytics platform
• Malware detection engine
• Data Lake query costs optimization system
• Technologies used: AWS Cloud Services, Git, PyTorch, Python, Scala, Serverless Framework, Spark, Terraform

Data Scientist/Data Engineer @ Marionete, Lisbon (October 2016–December 2018)

Design and implement Machine Learning use cases

• Documents indexation with search capabilities for compliance (Technologies used: AWS Cloud Services, Elastic Search, Python)
• Platform to match conference attendants (Technologies used: Heroku, Jenkins, Python, Pandas)
• Malware detection engine (Technologies used: AWS Cloud Services, Keras, Python, Scala, Spark)
• Partner trainer certified by Cloudera

Software Engineer @ SISCOG, Lisbon (September 2013–September 2016)

Model the domain of processes of planning railroad resources

• Intensive brainstorming of functionalities with the product managers
• Part of a development team for a new product with recent clients
• Technologies used: Lisp, ACL

🎤 Public Speaking

• Big Things Conference - From euros to zero: using Probabilistic Data Structures to reduce costs, Madrid (November 2020)
• MXNet Deep Learning Meetup - AI vs Malware: Threat Intelligence @ Work, Berlin (February 2019)
• Seminário Diagonal IST - Variable Selection in Football Squads, Lisbon (November 2011)

📚 Education

• Master (MSc) in Mathematics and Applications (Probabilistic and Statistics) @ Técnico, Universidade Técnica de Lisboa, Lisbon (2011-2013)
• Degree (BSc) in Applied Mathematics and Computation @ Técnico, Universidade Técnica de Lisboa, Lisbon (2007-2011)

📜 Master Thesis

• Title: The effect of an imperfect ground-truth in the evaluation of the performance of classifiers
• Supervisors: Prof. Maria do Rosário Oliveira
• Description: Link

⌨️ Programming Skills

🌎 Languages

🎨 Interests

• 🎮 Games: Playing games is an excellent way to relax
• ⚽️ Football: Everything
• 📺 Audiovisual Art: Films and TV Shows