Machine Learning Engineer

At TicketSwap, we're redefining the experience of buying and selling tickets. With a community of over 15 million users spanning 36 countries, our journey towards becoming the most trusted and preferred ticketing platform worldwide is well underway. Our mission? To ensure that every transaction is safe, fair, and effortless.

As we navigate the landscape of product innovation, we're confronted with an array of challenges - from developing groundbreaking features that delight our fans, to scaling our platform to new heights. Our drive stems from a deep-seated passion for technology and a relentless pursuit of providing the best fan experience.

TicketSwap is built by fans, for fans. Keeping them at the heart of everything we do is our guiding principle. We are continuously on the hunt for creative and intelligent people to strengthen our team.

Right now we are looking for a Machine Learning Engineer (MLE). The MLEs at TicketSwap work closely with the data team, product and finance. This provides the opportunity to focus on a wide variety of projects.

If you're passionate about machine learning and eager to contribute to a variety of meaningful projects, we'd love to hear from you. Join us in making the ticket buying and selling experience safer, fairer, and more enjoyable for fans worldwide!

What you'll do

This year, we're ramping up our machine learning efforts, focusing particularly on leveraging open source large language models to enhance our platform. Our MLEs play a critical role in shaping these initiatives from the ground up - from conceptualizing new ideas to bringing them to life through development, deployment, and ongoing optimization.
We're using on-premise hardware for model prototyping and development. Plus, our growing MLops infrastructure supports our team in experiment management, ensuring efficient tracking, smooth deployment, and meticulous monitoring of our models.

Key Responsibilities:

• Apply Machine Learning / Artificial Intelligence to personalization, discovery, fraud detection and natural language processing;
• Design Machine Learning solutions for TicketSwap’s unique product challenges;
• Manage models entire lifecycle from prototyping, to deployment, to continuous improvement and monitoring;
• Producing data insights: extract value from data and drive improvements and strategic decisions;
• Work closely with the different stakeholders, understand their problems and come up with solutions;
• Help with the continuing development of our MLops pipeline;
• With data driven decision making playing an important role the ML products you develop will have real impact on customers and the business.

About you

• Work experience as a Machine Learning Engineer or a Data Scientist;
• You are based in The Netherlands, are an EU resident, or have an existing visa to work here. A relocation package is not provided;
• Solid theoretical knowledge of Machine Learning;
• Familiarity with at least 2 of: Scikit Learn, TensorFlow/Keras, PyTorch, one of the llama or LLM ecosystems;
• Strong understanding of Python and OOP design principles;
• Good knowledge of data preprocessing and feature engineering;
• Comfortable with SQL;
• Ability to work with git, write code reviews, and tests;
• Passionate about building delightful products for users;
• Strong communication and team-work skills.

Nice to have

• Working experience with ETL and Data Pipelines;
• Familiarity with tools relevant to our workflow: AWS (S3, ec2, Redshift, SageMaker), ClearML, Hydra Framework, Docker;
• Experience with MLops beyond experiment tracking;
• Knowledge of statistics/statistical modeling.

Healthy lunch & snacks every day

Friday drinks at the office

Pension plan

Hybrid friendly work environment

Urban Sports gym membership

Diverse team with 30+ nationalities

TicketSwap is looking for the best and motivated talent out there no matter your nationality, gender, sexual preference or religious beliefs. 🚀

Research shows that women and those in traditionally underrepresented groups tend to apply only if they check all the boxes. That’s a shame, as we want to build a diverse and inclusive team. If you know you’ve got what it takes but don’t quite meet every requirement for the role, we still encourage you to apply.

Proactive acquisition from 3rd parties is not appreciated.