About us:
How did Web Summit become, in the words of Forbes, “the best tech conference on the planet”? Meaningful connections. Our tech events are unmissable because we make it easier for the right people to meet and connect. Everyone at Web Summit works towards this goal.
And we’re just getting started.
We’re always looking to build on the impact we have already made at Web Summit. In the coming years we’ll take Web Summit to new markets, promoting global connectivity, highlighting important issues and connecting global leaders – all while making a positive impact on the environment and communities we encounter.
To build a better company, we have to better ourselves. We do that by finding the most ambitious people to work with us.
We are seeking a versatile and innovative Applied AI/ML Engineer to lead the integration of Generative AI and machine learning into our product suite. This role is ideal for professionals who excel at transforming cutting-edge AI research into robust, user-centric applications.
Web Summits engineering team build in house software that powers all aspect of our attendees event experience, from native mobile applications, recommendation systems, and registration/tracking software to name a few.
What you will achieve:
Design, develop, and deploy scalable machine learning models, with a focus on Generative AI applications such as LLMs, diffusion models, and transformers.Collaborate with cross-functional teams—including product managers, data scientists, and software engineers—to integrate AI solutions seamlessly into products.Implement and optimize data pipelines for training and inference processes.Conduct rigorous testing and validation of models to ensure performance, reliability, and fairness.Stay abreast of the latest advancements in AI/ML to inform technology choices and innovation strategies. Skills and abilities we are looking for:
Proven experience in machine learning engineering, with a portfolio of deployed AI solutions.Proficiency in programming languages such as Python, and familiarity with ML frameworks like TensorFlow or PyTorch.Strong understanding of data structures, algorithms, and software architecture.Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization tools (e.g., Docker, Kubernetes).Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment. Nice to haves:
Advanced degree (Master's or Ph.D.) in Computer Science, Engineering, or a related field a plus but not essential.Experience with prompt engineering and fine-tuning of large language models.Familiarity with MLOps practices and tools for continuous integration and deployment of ML models.Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
