Machine Learning Engineering Lead at Lufthansa Technik
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
The Australian National University
Master of Computing, Artificial Intelligence
January 1, 2015 – January 1, 2017
Universidade de Coimbra
Master's degree, Computer Science
January 1, 2012 – January 1, 2013
Universidade de Coimbra
Bachelor's degree, Mathematics
January 1, 2007 – January 1, 2012
Lufthansa Technik
Machine Learning Engineering Lead
January 1, 2023 – Present
Frankfurt am Main, Hesse, Germany · Hybrid
zeroG - AI in Aviation
Machine Learning Engineering & Python Development Lead
February 1, 2022 – December 1, 2022
Frankfurt am Main, Hesse, Germany · Hybrid
Lufthansa Industry Solutions
Technology Consultant & Machine Learning Engineer
February 1, 2020 – January 1, 2022
Stuttgart Region
CRITICAL Software
AI & ML Engineer
November 1, 2018 – December 1, 2019
CRITICAL Software
AI & ML Engineer
December 1, 2017 – November 1, 2018
The Australian National University
Sessional Academic
February 1, 2017 – June 1, 2017
Canberra, Australian Capital Territory, Australia
onCaring
Junior Engineer
July 1, 2013 – January 1, 2015
Coimbra, Coimbra, Portugal
onCaring
Intern
October 1, 2012 – April 1, 2013
Coimbra
onAll
February 1, 2009 – Present
onAll is an easy-to-use wearable sensor system aimed at seniors with mobility risks and dementia in long-term care facilities that delivers real-time information about their condition and location allowing caregivers to rapidly assist them whenever and wherever needed.
Functional Programming Principles in Scala
Coursera
June 24, 2026 – Present
Rust Essential Training
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning academia and industry, with experience in multiple companies including Lufthansa Technik and CRITICAL Software. The project 'onAll' shows initiative and an interest in developing solutions for social good. The transition from Machine Learning Engineering Lead to a Data Analyst role would require a clear motivation, but the underlying analytical and technical skills are present. The breadth of experience suggests adaptability, but the direct alignment with a pure Data Analyst role (which often focuses more on reporting, visualization, and business intelligence rather than ML engineering) needs further exploration.
Soft Skills & Operational Fit
The candidate's experience as a Sessional Academic and in leadership roles suggests strong communication and mentoring skills. The project 'onAll' indicates an interest in applying technology to real-world problems, potentially aligning with problem-solving and innovation aspects of a data analyst role. However, specific details on collaboration and stress handling are not available from the provided data.