As a Staff Backend Engineer, you will architect and code video features across the video pipeline stack, lead the development of scalable video capabilities, mentor other engineers, and collaborate with multiple teams to enhance user experiences in live streaming and video processing.

The Senior Full Stack Software Engineer will lead the development of video functionalities such as live streaming and video storage. Responsibilities include collaborating with teams to enhance user experiences with video, developing backend video APIs, supporting video workflows, and mentoring other engineers in video technology.

As a Full-Stack Engineer, you will integrate advanced computer vision capabilities into the mobile app, primarily focusing on iOS development. You will collaborate with various teams to introduce machine learning models, ensuring seamless user workflows and maintaining high-quality software standards.

As a Product Design Manager, you will lead the design of consumer-focused products for youth sports. Your responsibilities include managing a design team, advocating for design excellence, driving collaboration across teams, and shaping the product direction. You'll apply your knowledge of sports and product design to create impactful user experiences.

The Product Marketing Manager will execute go-to-market strategies for a designated sport segment, providing market analysis to align products with strategic goals. Responsibilities include driving adoption, collaborating with product managers, prioritizing backlog, assessing market opportunities, and launching products through strategic thinking and data analysis.

As a Senior Product Designer, you will lead the design process for mobile and web platforms, collaborating with teams to create user-centered experiences. Your role involves conducting user research, defining design problems, and crafting intuitive design flows and prototypes while advocating for positive change within the design practice.

As an MLOps Engineer, you'll design and implement automated pipelines for deploying ML models, manage model life cycles, optimize cloud infrastructure, collaborate with various teams to ensure model performance, and develop reusable tools to simplify future deployments.