Senior AI Software Engineer

As a Senior AI Software Engineer at Avaloq, your primary responsibilities include leading AI experiments and developing solutions from ideation to production. You will collaborate with cross-functional teams to design and implement AI solutions tailored for the banking industry, ensuring that they cater to various user needs. Additionally, you'll deploy and maintain AI models in production environments, optimize these solutions for performance and scalability, and stay updated with the latest advancements in AI technology and regulations.

To qualify for the Senior AI Software Engineer role at Avaloq, candidates should hold a Master’s or Ph.D. degree in Computer Science, Engineering, or a related field. A strong background in data science, experimental thinking, and at least five years of experience in Full-Stack Software Development is essential. Furthermore, candidates should have at least one year of experience in developing Generative AI applications and fine-tuning Large Language Models (LLMs), along with proficiency in Python and familiarity with machine learning frameworks like TensorFlow or PyTorch.

At Avaloq, the work environment for a Senior AI Software Engineer is designed to be flexible and collaborative. We embrace a hybrid working model, allowing our engineers to maintain a healthy work-life balance while contributing to our innovative projects. Our culture is one of support and diversity, promoting an inclusive atmosphere where every team member can express their authentic selves and thrive in their careers.

As a Senior AI Software Engineer in our AI innovation lab, you'll work on groundbreaking projects aimed at enhancing operational efficiency within the financial industry. Specifically, you'll develop and implement personalized wealth management solutions using Generative AI technologies, focusing on real-world applications that align with the strategic objectives of our banking clients.

Avaloq is committed to the professional development of its team members. As a Senior AI Software Engineer, you will have access to opportunities for collaboration with some of the world's leading financial institutions, as well as ongoing training and workshops to keep your skills sharp. We encourage innovation and creativity, empowering our engineers to explore cutting-edge technologies and take ownership of their career trajectories within our organization.

When answering this question, be specific about which machine learning frameworks you've worked with, such as TensorFlow or PyTorch. Discuss projects where you've used these tools, emphasizing your role in deploying AI models and optimizing their performance.

In your response, highlight your understanding of AI ethics and responsible AI practices. Talk about how you integrate ethical considerations into your development process, including compliance with regulations and best practices to avoid biases in AI models.

Discuss specific projects where you've been involved in the development of Generative AI applications. Explain your contributions, the challenges you faced, and how you overcame them to deliver impactful solutions, focusing on relevant technologies and techniques applied.

When answering this question, narrate a particular AI experiment where you led the initiative. Describe the objectives, the approach you took, the results, and how it impacted the overall project or organization.

To demonstrate your commitment to ongoing learning, share the resources you utilize, like online courses, research papers, and industry conferences. Highlight specific topics or areas of AI that you're particularly interested in and how you apply this knowledge to your work.

Explain your approach to model optimization, such as tuning hyperparameters, regularization techniques, and leveraging advanced computing resources. Discuss specific tools and practices you implement to enhance performance and efficiency in production settings.

Describe your methods for fostering effective collaboration, such as establishing clear communication channels, using collaborative tools, and facilitating regular check-ins. Provide examples of successful projects where you effectively collaborated to achieve common goals.

Discuss your practical experience with cloud AI services like AWS, GCP, or Azure. Mention specific projects where you've utilized these services, emphasizing your role in implementing scalable and flexible AI solutions in a cloud environment.

In your response, emphasize your problem-solving skills and resilience. Share an example of a significant challenge you faced in an AI project, how you approached it, and the learning outcomes that emerged from the experience.

Share your insights about the evolution of AI in finance, touching on trends like personalization, operational efficiency, and risk assessment. Discuss how you envision contributing to this future through your work at Avaloq, emphasizing your interest in responsible AI practices.