Fabio Ellena
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
Senior Staff Software Engineer @ Stellantis
Staff Software Engineer and Technical Leader with 8+ years of experience building large-scale distributed systems and real-time platforms in the connected mobility domain. Currently at Stellantis, where I lead the technical evolution of cloud-native connected services supporting millions of vehicles worldwide. My focus is on designing resilient, scalable architectures, modernizing legacy platforms, and improving developer productivity across complex engineering ecosystems. I have led the consolidation of major enterprise platforms (FCA and PSA), designed near-real-time systems processing data from more than 10 million connected vehicles, and driven CI/CD modernization initiatives including migration from TeamCity to GitHub Actions. In recent years, I have also been actively integrating AI into software engineering workflows, introducing agentic development practices, AI-assisted code review, and automation across onboarding, testing, and system analysis. I am particularly motivated by environments where performance, precision, and engineering excellence are critical, especially where software directly impacts real-world systems operating at scale.
EURECOM
Master's degree, Data Science and Engineering
January 1, 2016 – January 1, 2018
Politecnico di Torino
Master's degree, Computer Engineering, Software
January 1, 2015 – January 1, 2018
Politecnico di Torino
Bachelor's degree, Computer Engineering
January 1, 2012 – January 1, 2015
Liceo Scientifico "Norberto Rosa"
High School, P.N.I (National Plan for Informatic)
January 1, 2007 – January 1, 2012
Stellantis
Senior Staff Software Engineer
October 1, 2024 – Present
Stellantis
Staff Software Engineer
March 1, 2023 – October 1, 2024
Stellantis
Technical Lead
February 1, 2022 – March 1, 2023
Concept Reply
Software Engineer
July 1, 2018 – February 1, 2022
Turin Area, Italy
DOCAPOST
Machine Learning Engineer
July 1, 2017 – January 1, 2018
Nice Area, France
Politecnico di Torino
Teaching Assistant
October 1, 2015 – July 1, 2016
Torino, Italia
Coolshop srl
Frontend Developer
April 1, 2015 – June 1, 2015
Torino, Italia
AI Race Telemetry Workbench
June 1, 2026 – Present
Local F1 telemetry workbench — imports FastF1 race data into TimescaleDB, served via a .NET Query API + MCP server, with a MAUI desktop replay UI and a grounded AI race analyst.
CityMUS
March 1, 2017 – July 1, 2017
Developed context-aware music recommendation system leveraging knowledge graphs (DBpedia) and Spotify API, demonstrating ability to combine diverse data sources for innovative solutions
Vehicle Routing Optimization
October 1, 2015 – February 1, 2016
Extended Jsprit (Java VRPTW solver) with custom balancing algorithm to minimize route variance across vehicle fleets. Led algorithm tuning and optimization against industry benchmark tests, improving solution quality for real-world routing problems.
Machine Learning DevOps Engineer Nanodegree
Udacity
June 24, 2026 – Present
Gradle Build Caching
Gradle Technologies
June 24, 2026 – Present
IELTS 7.5 (International English Language Testing System)
British Council
June 24, 2026 – Present
Generative AI Nanodegree
Udacity
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including music recommendation, F1 telemetry, and vehicle routing optimization, shows a broad interest in applying technical skills to various domains. Their experience in leading teams and defining engineering culture at Stellantis suggests a proactive and influential approach. However, the majority of recent experience is in general software engineering and leadership, with less explicit focus on core ML research or advanced model development, which might require a cultural adjustment for a pure ML Engineer role.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership and team-building skills from their Staff Software Engineer role. Their experience in defining Developer Experience standards and driving technical decisions indicates a focus on operational excellence and collaboration. The project descriptions suggest an ability to tackle complex problems and integrate diverse technologies.