Machine learning expert állások, munkák

• Writing and maintaining Python-based automated system and regression tests
• Expanding automated regression coverage and improving stability of test execution
• Evaluating daily automated test results and handling failures
• Owning and driving system-level testing activities within a Scrum team

• Shape and implement the company’s data science strategy and drive innovation, with a primary focus on Generative AI and Agentic workflows
• Identify opportunities to leverage data for business value and impact
• Take ownership of the full technical stack for development and deployment

• collaborating on the design and development of ML‑based applications and their backend components
• helping to select the most applicable solutions for a given business problem
• writing clean, efficient and well‑documented code
• contributing to our MLOps processes

• Monitoring of washing, cooling and lubricant systems of machines/equipment in the production area
• Coolant control, filling, refilling and documentation of machining machines
• Warehousing tasks, moving lubricants
• Professional operation of equipment and tools

• Design, development, and optimization of core ML models in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, code review and sharing best practices

• Design, build, and maintain large-scale distributed data systems
• Develop data processing pipelines using technologies such as Spark and streaming solutions
• Work on systems that evaluate and ensure the quality and integrity of large-scale knowledge graphs

About YES-EU YES-EU Group is a leading European service provider specialising in high-voltage systems and battery technologies. Founded in Scandinavia and headquartered in Switzerland, YES-EU operates a growing network of service centres across Europe — including Norway, Denmark, Finland, France,...

• Designing and developing new machine learning models with a focus on real-time performance
• Integrating cutting-edge ML features into the SkeleTRACK product
• Analysing model performance and identifying areas of improvement
• Mentoring junior engineers and driving technical discussions

• Integration of models into production systems
• Design of robust pipelines for real-time or batch data feeding into ML models
• Ensuring efficient model operation in production including speed, scalability, and memory usage

Design, train, and evaluate machine learning models for manufacturing use cases such as quality prediction, anomaly detection, predictive maintenance, and process optimisation, covering the full ML lifecycle from problem definition to performance tuning....

• Pioneer technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Gain new insights by bringing together rich semantic context with large scale business data.

You own the full lifecycle of machine learning models - from initial concept and experimentation through training and validation to reliable deployment on production-grade automotive systems....

Engineering Leadership: Lead, mentor, and manage distributed engineering teams across European hubs (including Norway, Finland, and Romania), overseeing performance and professional growth....

You develop advanced machine learning-based architectures for automated driving functions and shape the way in which we scale our ML development....

• Trusted advisor at the intersection of business strategy and data
• Ownership of full lifecycle from understanding client decision-making challenges to designing, building, and delivering BI solutions
• Lead client discovery and solutioning
• Own the information design layer

• Building and maintaining robust CI/CD pipelines for ML models and data workflows
• Automating and managing the end-to-end lifecycle of machine learning models from training to deployment and monitoring

• Design, develop, and optimize scalable data pipelines for processing large-scale structured and unstructured data
• Ensure reliability, performance, and scalability of data systems
• Build solutions to handle real-time streaming data from multiple sources

As a Machine Learning Engineer in our Retail ML team, you will take end‑to‑end ownership of designing, developing and maintaining advanced machine learning solutions that directly influence our commercial performance. Your work will span dynamic pricing, demand forecasting and data‑driven buying...

• Architect and implement cloud-native data solutions using GCP (BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer, Cloud Storage)
• Lead the design and development of complex data pipelines and distributed processing frameworks that ensure scalability, performance, and operational reliability

• You will actively work on sparsifying, pruning and quantizing CNN and transformer-based architectures for autonomous driving
• Design, implement, and evaluate models and training algorithms for runtime optimized 3D semantic occupancy predictions