Senior Machine Learning Engineer
Role details
Job location
Tech stack
Job description
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
Requirements
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., * 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
Benefits & conditions
We offer a diverse, multicultural, and mission-driven workplace where your impact truly matters. You'll join a collaborative team that values openness, respect, and work-life balance.
What you can expect:
- Flexible working hours and a hybrid model (with home office days).
- Up to 4 weeks per year working abroad, subject to policy and approvals.
- Paid training and volunteering days, plus charity donation matching.
- Health & fitness subsidy to support your well-being.
- Frequent team and social events that bring our global community together.
- A welcoming office environment with complimentary coffee, refreshments, fresh fruit, and healthy snacks.
- A company that embraces diversity and values different perspectives.
