David Batista
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Haystack OSS AI Framework Developer | LLM / NLP / ML Engineer | davidsbatista.net
I’m an experienced software developer and machine learning engineer with a strong background in Natural Language Processing. I’m skilled in applying Machine Learning, Deep Learning and other AI techniques to tackle diverse problems while also managing the associated software infrastructure ecosystem. My professional experiences span over academia, startup environments, freelancing projects, and established enterprises, where I’ve collaborated effectively with dedicated teams to deliver production‑ready software solutions. • Homepage: http://www.davidsbatista.net • GitHub: https://github.com/davidsbatista • Publications: http://goo.gl/uihrcx
Instituto Superior Técnico
Doctor of Philosophy (Ph.D.), Information Extraction and Natural Language Processing
January 1, 2011 – January 1, 2015
University of Lisbon
Master’s Degree, Information Extraction
January 1, 2007 – January 1, 2009
Karlsruhe Institute of Technology (KIT)
Erasmus student, Computer Engineering
January 1, 2005 – January 1, 2006
University of Lisbon
Bachelor’s Degree, Informatics Engineering
January 1, 2003 – January 1, 2007
deepset
Senior NLP Engineer
February 1, 2024 – Present
Berlin, Germany · Remote
Veeva Systems
Senior Data Scientist NLP - Link
March 1, 2023 – January 1, 2024
Berlin, Germany · Remote
Comtravo
Lead Natural Language Processing Engineer (acquired by TripActions/Navan)
May 1, 2022 – February 1, 2023
Berlin, Germany · Hybrid
Comtravo
Lead Natural Language Processing Engineer
May 1, 2021 – April 1, 2022
Berlin, Germany · Hybrid
Insecurity Insight
NLP Engineer
September 1, 2019 – October 1, 2019
Remote
Comtravo
Senior Natural Language Processing Engineer
August 1, 2017 – April 1, 2021
Berlin, Germany · Hybrid
HelloFresh
Data Engineer
January 1, 2016 – June 1, 2017
Berlin Area, Germany · On-site
INESC-ID
Researcher and Developer
June 1, 2011 – April 1, 2014
Lisbon Area, Portugal
LASIGE
Researcher and Developer
September 1, 2008 – October 1, 2010
Lisbon Area, Portugal
Nokia Siemens Networks
Software Developer
October 1, 2007 – July 1, 2008
Lisbon Area, Portugal
Faculdade de Ciências da Universidade de Lisboa
IT Technician (part-time)
November 1, 2004 – July 1, 2005
Lisbon, Portugal
Faculdade de Ciências da Universidade de Lisboa
System Network Administrator (part-time)
November 1, 2003 – March 1, 2004
Lisbon, Portugal
Politiquices.PT - http://www.politiquices.pt
October 1, 2020 – May 1, 2021
• A semantic graph connecting politicians through support/opposition relationships • Archived news articles support the graph relationships. • Awarded 2nd place on the ”Arquivo.pt Awards 2021” organised by the Portuguese Web Archive. • Gain the interest of journalists, political scientists and social humanities researchers. Technical description: • Data: news headlines from almost 25 years of Portuguese archived newspapers. • Developed supervised models to detect relationships between politicians. • Entity Linking between politicians mentioned in the headlines and Wikidata. • Semantic graph connecting politicians through relationships supported by news articles. • The graph is indexed in a SPARQL engine and published through a web interface
REACTION (Retrieval, Extraction and Aggregation Computing Technology for Integrating and Organizing News)
June 1, 2011 – April 1, 2014
• I took part in the REACTION (Retrieval, Extraction and Aggregation Computing Technology for Integrating and Organizing News) an initiative for developing a computational journalism platform (mostly) for Portuguese. • The project developed information extraction, social media mining and information visualisation technologies for assisting journalists in the production of news stories.
GREASE-II - Geographic Reasoning for Search Engines
September 1, 2008 – October 1, 2010
• I took part in the GREASE-II which researched information access methods to large collections of documents and objects having geographically rich text and meta-data, with emphasis on the web. • The geographic content of a document is characterized by geographic signatures, a set of automatically extracted geographic tags, mapped directly into ontologic geographic concepts. • The geographic signatures were evaluated in multiple scenarios, such as improving geographic retrieval methods and faceted interfaces for text and image retrieval applications.
Deploying Machine Learning Models in Production
DeepLearning.AI
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
B1 - Deutsch als Fremdsprache
Goethe-Institut e.V.
June 24, 2026 – Present
Statistical Learning
Stanford Online
June 24, 2026 – Present
Presenting Technical Information with Stories
June 24, 2026 – Present
Generative AI with Large Language Models
Coursera
June 24, 2026 – Present
Sustainable Software Engineering
Hasso Plattner Institute
June 24, 2026 – Present
Machine Learning Engineering for Production (MLOps) Specialization
DeepLearning.AI
June 24, 2026 – Present
Machine Learning School - LxMLS 2011
Instituto Superior Técnico
June 24, 2026 – Present
Machine Learning Modeling Pipelines in Production
DeepLearning.AI
June 24, 2026 – Present
Machine Learning Data Lifecycle in Production
DeepLearning.AI
June 24, 2026 – Present
Introduction to Machine Learning in Production
DeepLearning.AI
June 24, 2026 – Present
Emotional Intelligence: Cultivating Immensely Human Interactions
Coursera
June 24, 2026 – Present
AWS Essential Training for Developers
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project experience, ranging from academic research to industry roles in startups and larger companies, indicates adaptability. Their involvement in open-source contributions and a project like 'Politiquices.PT' suggests initiative and a passion for impactful work. The breadth of certifications, including language and soft skills, points to a continuous learning mindset. However, the target role is ML Engineer, and while the candidate has strong ML/NLP experience, the specific focus on 'ML Engineer' might require a broader ML system design perspective beyond just NLP, which is not explicitly detailed in all projects.
Soft Skills & Operational Fit
The candidate's experience in leading teams, defining annotation schemas, and managing sprint planning suggests strong organizational and leadership skills. Their involvement in open-source projects (Haystack) indicates a collaborative mindset. The certifications in 'Presenting Technical Information with Stories' and 'Emotional Intelligence' suggest an awareness and proactive approach to communication and interpersonal skills.