.Dotmoovs is a pioneering startup that combines advanced computer vision algorithms with a global competitive environment for sports. The platform leverages state-of-the-art artificial intelligence (AI) to analyze videos of users performing different exercises in real-time.This AI-based system functions as a virtual referee, assessing the performance of participants.The core concept of Dotmoovs revolves around bridging the gap between physical and geographical limitations in sports. It provides a unique solution for amateur athletes and sports enthusiasts to engage in competitive activities, regardless of their location. Users can challenge friends or similarly skilled players from anywhere in the world in their favorite sports.Locations SupportedThis role is on site, and requires you to spend your time in our office in Braga.About The Opportunity:Imagine being part of a cutting-edge team where your work not only contributes to the next big technological advancement but also shapes the future of how we interact with sports. At Dotmoovs, you're not just an engineer; you're a trailblazer atthe forefront of an exciting, evolving landscape. As a Machine Learning Engineer in our innovative team, you will play a crucial role in developing and improving our AI-driven system, enabling it to analyze and interpret user performance through video in real-time. Your success in this role will be marked by your ability to deliver scalable, robust, and efficient machine learning solutions. You will be a key player in advancing the machine learning models that power our products, contributing significantly to the technological advancement of our platform.What we offer:Competitive Salary + bonus (adjusted according to experience and achievements)Flexible and fast-paced environmentTeam events in very cool locationsShaping the future of sportsOther agreed tailored benefits to your needsResponsibilities:Technical Research and Model Development: Proactively research and implement cutting-edge machine learning models, especially in the areas of computer vision and deep learning, contributing to continuous improvements in our AI-driven solutions.Data Pipeline and Model Training: Design and build scalable data pipelines, manage training and testing of models, and ensure models are optimized for real-time performance.End-to-End Machine Learning System Management: Oversee the specification, development, training, deployment, and continuous monitoring of machine learning models to ensure they are performant and reliable in production environments.Code and Model Quality Assurance: Conduct thorough model evaluations and code reviews, sharing best practices with the team to maintain high-quality standards.Collaborative Teamwork: Work closely with product managers, data scientists, and engineers to integrate AI solutions into the broader system, ensuring seamless and reliable functionality