Senior Software Engineer - AI Applications

As a Senior Software Engineer - AI Applications at Ubisoft, your main responsibilities will include designing and developing scalable back-end systems that support AI applications, optimizing performance for low-latency and high-throughput operations, and collaborating with data scientists and ML engineers to ensure seamless integration of AI models. You'll focus on building cloud-native solutions, and your role will require you to mentor junior engineers and stay updated with the latest trends in AI and software engineering.

To qualify for the Senior Software Engineer - AI Applications position at Ubisoft, you should have substantial professional experience in software engineering with a focus on back-end development. Proficiency in programming languages such as Python, Java, Rust, or C++ is essential, along with hands-on experience in cloud platforms like AWS, GCP, or Azure. Additionally, knowledge of AI/ML integration in production environments, system architecture, and strong problem-solving skills are critical for success in this role.

Joining Ubisoft as a Senior Software Engineer - AI Applications opens up numerous growth opportunities. You can engage in continuous learning to stay updated with AI advancements, take on increased responsibilities, and influence the strategic direction of AI product offerings. You will have the chance to work on industry-leading projects and contribute to shaping the future of AI technology, all while driving impactful innovation within the company.

In your role as a Senior Software Engineer - AI Applications at Ubisoft, you will work with a variety of cutting-edge technologies. This includes programming languages like Python and Java, cloud platforms such as AWS or Azure, and containerization technologies like Docker and Kubernetes. Furthermore, you will engage with large language models, hybrid search systems, document processing, and AI/ML integration, ensuring that your skill set is both robust and diversified.

The work environment for a Senior Software Engineer - AI Applications at Ubisoft is collaborative and inclusive, situated in the vibrant office located in Saint-Mandé. With a strong focus on innovation and creativity, you will have the flexibility of hybrid working arrangements according to company policies. You’ll be surrounded by talented individuals who value diverse perspectives, making it an exciting opportunity to contribute to significant projects while enjoying perks such as comprehensive healthcare and generous paid time off.

In approaching back-end system design for AI applications, I start by understanding the requirements of the application, including scalability and performance needs. I prioritize modular architecture to promote maintainability and use microservices to allow for independent deployment. I also focus on the integration of AI models, ensuring a seamless flow of data and low-latency access for end-users.

To ensure the performance of AI models in production environments, I emphasize rigorous testing and optimization processes. I monitor model latency, throughput, and resource usage, and employ strategies such as caching results or optimizing the underlying algorithms. Implementing proper load balancing and auto-scaling solutions in the cloud infrastructure also plays a crucial role in maintaining reliable performance.

My experience with cloud platforms like AWS and Azure involves deploying applications and managing cloud infrastructure. This includes using services such as AWS Lambda for serverless computing, Azure Functions for event-driven architectures, and integration with databases and AI services. I have also worked on optimizing costs and enhancing security within cloud environments while ensuring high availability.

I am most comfortable using Python and Java for back-end development because of their rich ecosystems and strong support for building complex applications. Python's simplicity and extensive libraries make it ideal for rapid development, while Java's performance and robustness are beneficial for large-scale applications. I also have experience with C++, which I use when performance is critical.

My approach to problem-solving in complex software environments involves breaking down issues into manageable parts and analyzing them systematically. I use diagnostic tools to pinpoint the root causes and collaborate with team members to gather different perspectives. I also prioritize creating high-level designs and prototypes to validate solutions before full implementation.

I have extensive experience with AI and machine learning integrations, including deploying models in production and serving predictions via APIs. My background involves working with frameworks like TensorFlow and PyTorch to build models, as well as leveraging pre-trained models for specific applications. I also have dealt with challenges like feature engineering and model update strategies in live environments.

In a recent project, I optimized a back-end system by introducing microservices architecture and asynchronous processing patterns. I found that our monolithic design was causing bottlenecks, so I restructured the system, which reduced the response time by 50%. Additionally, I integrated caching layers and optimized database queries, leading to significant performance improvements.

I actively stay current with the latest trends in AI and cloud computing through various channels. I regularly read technical blogs, attend webinars, and participate in online courses to enhance my knowledge. I'm also involved in developer communities and open-source projects, which provide insight into real-world applications and emerging technologies.

Yes, I have mentored junior engineers by encouraging hands-on learning through guided projects. I focus on sharing knowledge through code reviews, pair programming, and fostering an environment where questions are welcomed. My mentoring approach centers on balancing technical skills with soft skills, empowering them to grow and take ownership of their work.

I believe the future of AI applications in gaming holds fantastic potential, particularly in creating more immersive and intelligent gameplay experiences. As AI continues to advance, we will see more refined NPC behaviors, adaptive difficulty levels, and personalized gaming experiences driven by user interactions. The integration of AI will not only enhance gameplay but also streamline development processes, paving the way for innovative game design.