Machine Learning Engineer

• Design, train, and optimize deep learning models for computer vision tasks in highly dynamic and safety-critical environments
• Own the full ML lifecycle, from data strategy and model architecture to deployment and performance monitoring
• Develop robust evaluation pipelines to ensure models meet strict reliability and safety requirements
• Work on ML certification activities, validating model behavior under defined regulatory frameworks
• Leverage transfer learning and simulation to scale training and testing beyond real-world data limitations
• Collaborate closely with software, systems, and flight teams to integrate ML models into real-world applications
• Continuously push model performance across edge cases, environmental variability, and operational constraints

NLP Engineer

• Drive Research: Lead experiments to answer cutting-edge research questions, designing evaluations and analyzing results
• Innovate: Explore novel approaches and emerging technologies that advance TR's product portfolio
• Collaborate & Disseminate: Work with experienced research scientists and share your findings through internal presentations and external publications

Research Intern – Machine Learning, Natural Language Processing

Computer Vision Engineer

• **What You´ll Do**
• - Develop and implement computer vision algorithms and deep learning models for localization and mapping, object detection and tracking, classification, general image processing, and related functions - as well as analyze, extend, and improve the existing code base and models.
• - Collaborate with other engineering teams (such as flight testing, hardware, sensor fusion) to integrate computer vision solutions into prototypes and products.
• - Test and evaluate the performance, robustness, and reliability of computer vision systems in diverse conditions, to ensure accuracy, reliability, and efficiency. This may involve both simulated and real-world environments.

• Develop, apply, and advance machine learning solutions for personalization use cases
• Design experiments, evaluate model performance, and use data-driven methods to improve relevance, ranking, recommendation, and overall customer experience
• Partner across engineering, product, analytics, and science teams to define solution approaches, influence technical direction, and deliver ML capabilities
• Contribute technical depth in model development, feature design, data preparation, offline and online evaluation
• Apply strong technical judgment to system design, API design, data modeling, and low-level solution design
• Safely integrate and operate AI/ML-enabled solutions

Machine Learning Scientist III, Personalization

• Design, develop, and apply machine learning solutions to real-world personalization, product, and business problems
• Drive end-to-end scientific work across problem formulation, data exploration, feature engineering, model development, evaluation, and iteration
• Partner closely with engineers, product, and business stakeholders to integrate machine learning solutions
• Use strong technical judgment to select appropriate methods, validate outcomes, and improve model performance
• Safely integrate and operate AI/ML-enabled solutions
• Contribute deep technical expertise across related domains

Senior Machine Learning Scientist, Personalization

AI Engineer

• As a Staff Machine Learning Engineer, you will own the most technically complex and high-impact projects from conceptualization over architecture design to production deployment.
• You will:
• - Set direction for a technical team, ensuring architectural excellence and long-term solution maintainability.
• - Lead and mentor junior and senior engineers, raising the technical bar across projects.
• - Stay hands-on with high quality code contributions to data processing, modeling and deployment pipelines while delegating effectively.
• - Partner with clients to translate complex business challenges into clear technical roadmaps and deliver measurable business outcomes.
• - Drive adoption of modern ML best practices and state-of-the-art methodology from system design and architecture over modelling to MLOps.
• You are not only passionate about machine learning, but also about shaping how data-driven insights create value for our clients. You thrive in dynamic environments, balancing hands-on technical work with strategic decision-making and team leadership.
• This role goes beyond building models: you will be responsible for technical strategy, quality standards and growing engineering talent, shaping the future of our ML delivery practice.

Staff AI Engineer

• Discovery & Process Design: Facilitate workshops to understand existing business processes and identify pain points
• Project Setup & Orchestration: Technical implementation of the project and definition of milestones
• Hands-on Implementation: Build data structures, implement AI intelligence, and develop the user interface
• Iterative Optimization: Present prototypes and refine the solution until achieving optimal automation

AI Product Builder, Fullstack AI Engineer, Implementation Lead

• Join the company’s growing team and take part in our expansion in Switzerland and internationally.
• As a Senior Machine Learning Engineer, you will be working on a variety of applied research projects using state-of-the-art Machine learning techniques and you will help deploy them for people to leverage their outputs.
• You are passionate about understanding the business context for features built to drive better customer experience and adoption.
• Finally, you are meticulously organized and prepared to work in a fast-paced and dynamic team environment.

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