Machine Learning Engineer
Role details
Job location
Tech stack
Job description
We are looking for a Senior Machine Learning Engineer in Stockholm, Hamburg or Berlin (Hybrid) to join our central AI/ML Hub and collaborate closely with game studios and other central hubs (Data, Marketing, Ads) to build solutions that drive player experience, operational efficiency, and long-term business impact.
We are at a pivotal stage in scaling AI and ML across the Stillfront Group, with a clear ambition to accelerate and consolidate our efforts in order to make AI and ML a fundamental part of our DNA. This role will be a key enabler in that effort.
This position sits at the intersection of applied machine learning, software engineering, and business problem-solving, helping studios go from experimentation to reliable, scalable ML in production.
As our Senior Machine Learning Engineer, you will be responsible for delivering end-to-end ML solutions, establishing shared tools and workflows, and supporting teams across the organization in adopting ML best practices. You will play a critical role in shaping how ML is built, deployed, and operated across the Stillfront portfolio.
YOUR MISSION
- Lead the design, development, and deployment of production-grade ML models, primarily for personalisation and LiveOps management.
- Own ML systems end-to-end, including data preparation, training pipelines, inference services, monitoring, and iteration.
- Support the development of a central ML platform to enable scalability through reusability and standardization of development workflows.
- Translate product and business problems into scalable ML solutions, balancing model quality, performance, and cost.
- Help define and implement best practices for model lifecycle management, versioning, evaluation, and retraining.
- Collaborate with data engineers and backend engineers to integrate ML systems into live products.
- Mentor and support other ML engineers, helping raise the overall ML maturity of the organization.
- Be our main ML advocate and promote internal knowledge sharing that helps build our AI/ML community.
- Stay up to date with applied ML and MLOps practices and assess their relevance for Stillfront's needs.
Requirements
- 6+ years of experience as a Machine Learning Engineer or similar role, with a proven track record of shipping ML models to production.
- Degree in Computer Science, Data Science, Mathematics or related quantitative disciplines.
- Hands-on experience throughout the full ML lifecycle: from data exploration and feature engineering to deployment and monitoring.
- Strong grounding in machine learning fundamentals and algorithms, with demonstrated ability to select, tune, and evaluate models for real-world problems.
- Solid programming skills, especially in Python, SQL and large-scale data processing languages, as Spark. And experience with common ML frameworks and libraries (e.g. scikit-learn, PyTorch, pyspark, TensorFlow).
- Experience integrating ML models into production systems via APIs, batch jobs, or streaming pipelines.
- Experience contributing to collaborative codebases using Git and familiar with best practices.
- Familiarity with cloud-based environments and production infrastructure, preferably GCP.
- Pragmatic and impact-driven, with the ability to operate in ambiguous environments and turn loosely defined problems into shipped solutions.
Nice-to-have experiences
- Experience contributing to internal ML platforms or shared ML infrastructure.
- Familiarity with MLOps practices such as experiment tracking, CI/CD for ML, and model registries.
- Prior experience in gaming, consumer products, or large-scale data environments.
- Experience mentoring or guiding other engineers in ML-related work.
Benefits & conditions
- Autonomy to explore and implement new technologies, tools, and processes.
- Competitive salary and comprehensive benefits package.
- Work in a dynamic environment with high exposure to a wide variety of genres, tools, and diversified products.
- Flexible working hours and a supportive, collaborative work environment.
- Opportunity to work with a talented team of professionals and make a significant impact on a globally recognized product.