Algorithm Developer in Mathematical modelling

About the role

Do you want your engineering skills to directly shape how athletes understand and improve their movement? Are you excited by the opportunity of turning noisy, high-dimensional data into clean, actionable biomechanical metrics used by professionals and ambitious amateurs alike? We are looking for an Algorithm Developer in Mathematical modelling to join our Motion Analysis team. You'll work at the intersection of deep learning and real-world sports science, taking the raw output of our AI models and building the modelling and post-processing pipelines that make the data real. This is where the engineering meets the athlete. As a member of our team, you will be responsible for the key step between AI prediction and product output. Our deep learning models produce body key points from video. Your job is to turn those noisy, uncertain estimates into robust skeletal fits and reliable biomechanical metrics that our users can trust and act on. We believe it takes careful post-processing and modelling to turn raw deep learning predictions into data that is real, reliable, and actionable. You will design and develop custom algorithms that handle outlier detection, optimization, and human body model fitting, often as one integrated modelling approach rather than separate steps. You will be part of an agile, collaborative team, contributing to solutions from prototype to production and helping shape our products. You will join a team of six, with diverse backgrounds spanning deep learning, computer vision, software engineering, and mathematical modelling. We work in a collaborative environment where team members support each other and share responsibility for moving projects forward. We believe that strong solutions emerge through open dialogue across disciplines. We also value a positive and engaging work environment, where curiosity is encouraged and people can explore problems that interest them alongside supportive colleagues. Your primary responsibilities will include: Designing and implementing mathematical models that fit skeletal structures to noisy key point data, balancing input uncertainty with anatomical constraints. Developing robust outlier detection and rejection methods that work within the modelling framework, not just as a pre-processing step. Building and refining optimization pipelines for post-processing deep learning outputs into accurate biomechanical metrics. Conducting data analysis and statistical validation to understand model performance and propose improvements. Collaborating closely with our deep learning engineers and software engineers to ensure your models integrate cleanly into the broader product pipeline. Exploring and evaluating new approaches from research literature, adapting them to our specific problem domain and data characteristics. A master's degree or PhD in Applied Mathematics, Physics, Engineering, Signal Processing, or a related technical field with strong mathematical foundations. Solid skills in mathematical modelling, you are comfortable formulating real-world problems as optimization, estimation, or fitting problems. Strong foundations in linear algebra, statistics, and numerical methods. Experience working with noisy, real-world data,you understand uncertainty and know how to handle it. Programming skills in Python - Familiarity with C++ is a plus. You have an entrepreneurial mindset and are driven by making your work matter in a real product, not just in a report. Communication skills, with the ability to explain mathematical choices to colleagues from different technical backgrounds. Preferably: Experience with signal processing methods such as filtering, smoothing, or time-series analysis. Familiarity with constrained optimization techniques and solvers. Experience with human body modelling, biomechanics, or motion capture data. Exposure to deep learning, not necessarily training models, but understanding what they output and why they fail. A genuine passion for applying mathematical thinking to solve real-world challenges. An interest in sports like golf, baseball, or others is a bonus! The Office We are located at DTU Science Park in Hørsholm. We take great pride in the state-of-art building we have designed! The office features bright meeting rooms, coffee areas to catch up with colleagues, a large testing arena with simulators available for employees and a fitness center, everything surrounded by a beautiful forest and respecting the environment. We made sure to utilize the newest technologies to be energy efficient and be mindful of ventilation and sound propagation. The cherry on top is our canteen: with an indoor and outdoor area to enjoy the fresh food prepared by our own kitchen staff. Join the home of a powerful sports brand and a one-of-a-kind technology Our proprietary technology is based on expert knowledge about radar, computer vision, data, and software engineering. Our solutions are developed by specialists who endlessly explore and challenge new t

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