About You
Are you looking for an opportunity to work on meaningful, cutting-edge projects in machine learning? Did you wonder what it would be like to work at a company where your contribution has a real, measurable impact – and you are rewarded for it?
If you have a knack for data and aspire to contribute to ethical tech development, then this is the perfect role for you! We value autonomy, allowing you to bring your innovative ideas to fruition in an inclusive, feedback-oriented environment. Your work on NLP will directly contribute to advancing corporate responsibility through technology.
Your Responsibilities
As our new Machine Learning Engineer, you will play a key role in developing state-of-the-art Machine Learning applications within RepRisk’s Entities team. You will contribute to the design, implementation and operation of Machine Learning products as part of our global Data division. Moreover, you will:
Design and implement new ML features that deliver measurable business value
Build and optimize multifaceted search engines that aggregate and search data across multiple sources (meta-search)
Develop, integrate, and maintain microservices within larger applications
Apply the latest advancements in ML, including Large Language Models (LLMs)
Train, evaluate, and optimize models for performance, scalability and reliability in production environments
Collaborate closely with other ML engineers, backend engineers and product owners to continuously improve the products
Contribute to a well-balanced tech stack, prioritizing both simplicity, maintanibility and efficiency
Ensure clean, high-quality code through thorough code reviews and engineering best practices
Actively participate in Agile/Scrum processes, contributing insights and feedback
You Offer
Master's degree (preferred) in Computer Science, Engineering, Statistics, or a related STEM field
3+ years of hands-on experience as an ML Engineer in a production environment
Expert-level Python skills and solid proficiency in SQL
Proven experience developing and deploying NLP models, information retrieval systems, and search engines
Hands-on experience integrating AI and LLMs into ML pipelines
Strong foundation in software engineering best practices, with a focus on clean, maintainable and scalable code
Experience working with cloud platforms, CI/CD workflows, and containerized environments
Proactive mindset with the ability to take ownership and drive solutions forward
Strong analytical thinking, structured problem-solving, and highly efficient execution
Excellent communication skills and fluency in English
Additionally, the following are a plus:
Experience in low-code languages like C++ or Java
Experience working with AWS, particularly SageMaker
Prior experience fine-tuning or training LLMs
Practical experience building and managing data pipelines
Please note that we will only consider candidates with a valid work permit.
