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 a Senior Machine Learning Engineer, you will play a key role in developing and scaling 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 advanced ML features that deliver measurable business value, taking end-to-end ownership from ideation to production
Architect, build, and optimize multifaceted search engines that aggregate and retrieve data across multiple sources (meta-search)
Design scalable system architectures and drive technical decisions to ensure long-term maintainability and performance
Develop, integrate, and maintain microservices within larger applications
Apply and guide the adoption of the latest advancements in ML, including Large Language Models (LLMs)
Train, evaluate, and optimize models for performance, scalability, and reliability in production environments
Mentor and support other ML engineers, fostering a collaborative and high-performing engineering culture
Collaborate closely with ML engineers, backend engineers and product owners, to continuously improve the products, acting as a technical lead in cross-functional initiatives
Contribute to a well-balanced tech stack, prioritizing both simplicity, maintanability and efficiency
Ensure high-quality, maintainable code through thorough code reviews and engineering best practices
Actively contribute in Agile/Scrum processes, sharing insights and feedback
You Offer
Master's degree (preferred) in Computer Science, Engineering, Statistics, or a related STEM field
5+ years of hands-on experience as an ML Engineer in a production environment
Expert-level Python skills and strong 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
Proven track record of designing and delivering scalable, production-grade ML systems and architectures
Experience working with cloud platforms, CI/CD workflows, and containerized environments
Experience leading technical initiatives, with a high degree of ownership and accountability
Strong mentoring skills and ability to support and guide more junior team members
Proactive mindset with the ability to take ownership, drive solutions forward, and navigate ambiguity
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.
