Senior Software Engineer, Sports AI - Genius Sports - Remote - Global

We’re looking for a Senior Software Engineer on our Sports AI team to help build the next generation of real-time AI systems powering sports analysis and insights. These systems transform live sports broadcasts (incorporating signals from video, crowd noise, audio commentary, and text) into a structured understanding of game context and auto-generated insights. The outputs from these systems power a range of products including automated highlight clipping, augmented broadcasts, semi-automatic play-by-play collection, and natural-language insight generation. For example, these systems can detect a goal, attribute it to the correct player, and localize where it occurred on the pitch within seconds by combining crowd noise spikes, commentary signals, and video cues. This role sits at the intersection of streaming and distributed systems, AI, and product engineering. You’ll build and operate real-time pipelines that process noisy, asynchronous inputs under tight latency constraints. These systems combine traditional streaming and data processing techniques with modern multimodal AI models to produce reliable outputs in production. You’ll work on challenges like aligning signals across multiple sources, handling uncertainty and inconsistency in model outputs, and designing systems that degrade gracefully in real-world conditions. We are early in building these capabilities, so the role involves working through ambiguity, experimenting with different approaches, and building new systems from first principles where established patterns don’t yet exist. Key Responsibilities include designing, building, and operating real-time streaming systems, ingesting and synchronizing signals, integrating AI models, designing evaluation frameworks, developing mechanisms for uncertainty handling, owning systems end-to-end, collaborating with partners, and mentoring engineers. Qualifications include 5+ years of experience, strong fundamentals, experience with streaming and distributed systems, ability to evaluate system quality, product-mindedness, interest in AI, and adaptability. Preferred qualifications include experience with LLMs, human-in-the-loop workflows, streaming tools, media protocols, media processing, sports background, and Rust. Salary: $160,000–$230,000 USD annually.