Software Engineer, GeniusIQ

Genius Sports•Los Angeles, CA

16d•$160,000 - $180,000•Hybrid

About The Position

We are looking for a software engineer to work on the systems and applications that power our automated, real-time GeniusIQ products. You will collaborate with Computer Vision and AI/Machine Learning teams to take models from research to production, ensuring they run reliably and efficiently in live environments. This includes building the services, orchestration layers, configuration tooling, monitoring and alerting systems, and internal operator interfaces required to manage, visualize, correct/enrich, and scale our automated data pipelines across thousands of global sporting events each year.

Requirements

Experience operating distributed systems.
Experience building real-time, interactive web frontends.
Experience designing APIs and integrating services.
Experience managing relational databases (schema design, indexing strategies, query optimization, performance tuning, migrations, and availability considerations).
Bachelor’s degree in Computer Science or equivalent experience.

Nice To Haves

Rust, Elixir, TypeScript, Go, C++, Python
Postgres, relational databases
React, Three.js, HTML5 Video, and/or Canvas
REST, GraphQL, and gRPC APIs
Systems that run inference with Computer Vision or AI/Machine Learning models
AWS, Temporal.io
Docker, Kubernetes
Pulsar, RabbitMQ
WebAssembly

Responsibilities

Design and develop systems and applications that power our automated, real-time GeniusIQ products including tracking data, analytics and event feeds, video products, and officiating technologies.
Own and implement features end-to-end across the stack, taking responsibility for the system lifecycle from configuring and managing on-premise hardware through reliable, real-time delivery of critical products to customers.
Lead technical discussions, drive architectural decisions, and identify opportunities to improve scalability, automation, and operational efficiency as we expand across new leagues and sports globally.
Design and maintain the foundational GeniusIQ platform that powers our live systems and supports development & iteration by other engineering teams building on this platform.
Design and improve testing and release strategies for complex, distributed systems — including backend services, web applications, data pipelines, messaging and streaming services, real-time model inference systems, and on-site hardware components.
Monitor, analyze, and continuously improve system performance, reliability, and scalability. Build solutions for simulating and replaying live inputs, system and metadata validation, automated evaluation and regression testing, and observability and alerting.
Design and build mechanisms for enabling human or agent-in-the-loop workflows that validate, correct, and enhance outputs from the system.