Meet Xavier, a 40-year-old Research Engineer at Meta, based in Angers, France. His path from Le Wagon to Meta illustrates the transformative power of learning and adaptation in tech careers. Xavier shares insights into his journey, from shifting roles to focusing on cutting-edge AI research.
Can you please introduce yourself?
I am Xavier, a Research Engineer at Meta, working on the Llama program. After discovering coding at age 34 and graduating from Le Wagon, I pivoted from Product Management to Software Engineering. I seized an opportunity at Meta’s AI lab, FAIR, where I dove into groundbreaking projects like Llama.
Can you tell us about your career journey?
After being a Product Manager and then a Management Consultant, I was at a crossroads in my career. Many of my friends had founded successful startups, and I thought I could follow their path. I joined Le Wagon with the goal of kick-starting my own business. However, during the bootcamp, I discovered a passion for the technical side of things over the business side. Back when I was a student, programming wasn’t considered cool and being called a ‘geek’ was an insult. Fast forward 15 years, and the perception had totally changed, so I was ready to embrace my ‘geek coming out.’
A friend of mine, one of these successful entrepreneurs, suggested I try getting into a Big Tech company. I took a year off to gain hands-on experience at a friend’s startup, read tons of books, and then applied my knowledge. I received offers from both Google and Meta. The only engineering positions at Meta in Paris were at FAIR, the AI lab, which is how I entered the field. Luck played a significant role!
My last project at FAIR involved theorem proving, quite a niche area. However, some team members decided to build a large language model to power our work, which became Llama. Once again, I was lucky to be in the right place at the right time.
What motivated you to switch from product management to software engineering, and then to focus specifically on AI research?
My transition to software engineering was driven by a newfound passion for coding ignited during Le Wagon. Joining Meta’s FAIR team was serendipitous—it allowed me to explore AI research, where innovation thrives.
How did your experience at Le Wagon contribute to these career transitions? Are there any specific aspects of the bootcamp that were particularly beneficial?
Le Wagon sparked my coding enthusiasm and empowered my career shift. Its practical curriculum and immersive approach equipped me with the confidence to pursue software engineering and AI research at Meta.
What does your current role as a Research Engineer at Meta involve? Can you share any exciting projects you’re working on?
I focus on advancing the Llama models at Meta, a project I’ve been deeply involved in since its inception. From training to modelling, it’s been a thrilling journey pushing AI boundaries.
From your perspective, how is AI transforming the tech industry and creating new opportunities for professionals?
AI automates tasks and opens new avenues, yet challenges like model limitations persist. Specialized, smaller models might revolutionize AI applications, reshaping tech roles.
What new opportunities do you see emerging for software engineers and AI researchers as AI technology continues to evolve?
AI-driven changes in coding and automation will demand deeper understanding and specialization. Coding has evolved with AI, making it easier and more efficient. However, it also increases the need for quality control and strategic application. Repetitive tasks will be automated, and there will be a growing need for professionals who can design systems and orchestrate workflows to leverage AI effectively. This blend of technical expertise and strategic AI application will drive innovation and efficiency in the tech industry.
How do you think the integration of AI is influencing the future responsibilities and skill sets of software engineers?
Just as software engineers need a basic understanding of networking and databases, they will need a similar level of understanding of AI. Not all of us will be AI specialists, but we will all need to interact with AI systems. It’s important to have a mental map of how these systems work to effectively integrate and utilize them in our projects.
What advice would you give to potential students or recent graduates interested in pursuing a career in AI or transitioning between roles in the tech industry?
Focus on core principles—deep understanding trumps chasing trends. Read comprehensively and apply knowledge practically to excel in AI and tech.
Xavier’s journey—from Le Wagon to Meta—exemplifies the transformative impact of technical education and career transitions in the tech industry. His insights into AI research and software engineering illuminate the evolving landscape of tech careers, emphasizing continuous learning and adaptability as catalysts for success.
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