Machine Learning Engineer
Description For Machine Learning Engineer
Trustly, a leading fintech company revolutionizing human-centric payments, is seeking a Machine Learning Engineer to join their Data domain within the Product and Tech function. This role is crucial in transforming Trustly into a truly data-driven organization, focusing on building and deploying machine learning models that drive critical business decisions.
As a Machine Learning Engineer, you'll be responsible for developing end-to-end ML pipelines, managing data infrastructure, and ensuring high-performance model deployment in production environments. You'll work with cutting-edge ML applications and take ownership of complete machine learning lifecycles, from development to deployment and monitoring.
The role offers an opportunity to work with a multidisciplinary team in a rapidly growing global company that connects thousands of businesses with hundreds of millions of people across Europe and the Americas. You'll be part of a team responsible for every aspect of the data journey, from collection & modeling to analysis and visualization, providing the entire organization with data and analytics artifacts to improve decisions, operations, and customer experience.
The ideal candidate should have a strong technical background with 5+ years of experience in ML model deployment, a Master's degree in a relevant field, and expertise in various ML frameworks and tools. You'll need to be proficient in programming languages like Python and Java, have experience with ML Operations, and be familiar with cloud platforms and big data tools.
Join Trustly if you're passionate about ML and AI, problem-solving, and building scalable solutions in a dynamic fintech environment. The company values innovation, great communication, and people who voice and act on new ideas. This hybrid position in Stockholm offers an exciting opportunity to be at the forefront of payment technology innovation.
Responsibilities For Machine Learning Engineer
- Develop end-to-end pipelines to deploy machine learning models into production environments
- Build and maintain efficient data pipelines for data collection, preprocessing, and feature transformation
- Monitor and evaluate feature drift and performance of deployed models
- Work closely with data scientists, software engineers, architects and product managers
- Keep up with the latest advancements in machine learning and AI technologies
Requirements For Machine Learning Engineer
- 5+ years of hands-on experience developing and deploying machine learning models in production
- Master's degree in Computer Science, Engineering, Mathematics, or related field
- Proficient in programming languages like Python, Java, or C++
- Experience with ML frameworks such as Sagemaker, MLFlow, TensorFlow, Keras, PyTorch
- Strong understanding of machine learning algorithms, statistics, and optimization techniques
- Experience working with ML Operations, model lifecycle, and CI/CD pipelines
- Familiarity with cloud platforms like AWS, Google Cloud
- Experience with big data tools and distributed computing
- Experience working with streaming data pipelines in Kafka
- Knowledge of version control systems and containerization tools
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