Senior Machine Learning Engineer

WHO WE AREThe Trustly Americas team combines PayWithMyBank, a 2012 Silicon Valley startup, with Trustly AB of Sweden, following their 2019 merger. Our team represents 30 nationalities, serving 8,300 merchants, connecting to 650 million consumers, and 12,000 banks across 33 countries. Our global network processes over $42 billion annually.
Our digital account-to-account platform redefines the speed, simplicity, and security of payments. Consumers pay for purchases by simply signing into their bank accounts, bypassing the card networks, and never leaving a merchant’s site or app – no credit card numbers or separate account setup necessary. With offices in Vitoria, Brazil, Silicon Valley in the US, and global headquarters in Stockholm, Sweden, we are a culturally diverse team. 
At Trustly, we believe that inclusion and diversity are essential foundations for building a fair and equitable society. We do not discriminate based on race, religion, ancestry, color, national origin, gender identity, sexual orientation, age, citizenship, marital status, or disability status. Our main goal is to provide a fair, welcoming, diverse environment with opportunities for all collaborators. The stages of our selection process take place online and without distinction of any kind.
It’s a great time to join Trustly as the Americas team is growing fast. If you thrive in an entrepreneurially-minded, fast-paced, casual, professional, positive, and rewarding work environment, check us out!
About the teamThe Risk team is responsible for maintaining the risk controls at Trustly, developing machine learning models and data analysis aiming to mitigate risk. The Machine Learning Engineer works together with the Risk Data Science and MLOps teams to process large volumes of data and implement AI models on a production scale. Our mission is to create a framework and infrastructure to manage risk and create long-term competitive differentiation and value for Trustly.

What you'll do:

• Collaborate with data science and engineering teams to build Machine Learning solutions.
• Define the architecture of reproducible, scalable, and monitored ML solutions for the production environment, ensuring good systems architecture practices;
• Architect and develop retraining pipelines;
• Assist other teams in recurrent execution pipelines following good Data Engineering practices;
• Expose machine learning models in a scalable and highly available way for use in a production environment;
• Optimize prediction time performance of our machine learning models;
• Manage the lifecycle of machine learning models for tracking parameters, metrics, and artifacts ensuring good data science practices;
• Help drive optimization, testing, and tooling to improve data quality;
• Improve our deployment process and automated test features.

Who you are:

• Large experience in machine learning product development;
• Experience leveraging large-scale data processing technologies;
• Experience with Python and ML libraries (Scikit-learn, Pytorch, Tensorflow, Pandas, Numpy, etc);
• Deep knowledge and understanding of Machine Learning algorithms and how they work (classification, regression, clustering);
• Experience with AWS (Sagemaker, EC2/ECS, S3, EMR);
• Experience with Big Data tools and ecosystems (Spark, Hadoop, etc);
• Knowledge of software development best practices and architectural patterns;
• Skills in algorithms, data structures, and relational databases (SQL is required);
• Advanced English level;
• Be located in Portugal.

Check out our Life page on Linkedin or our Glassdoor for more details about us, our culture, and much more.
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