About the Role:

As a Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi.

A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine.

You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams.

We currently have multiple openings;

• Staff Software Engineer
• Principal Software Engineer
  • Additional Details: As a Principal Engineer on the ML Infrastructure team, you will be a technical leader and visionary, driving the evolution of our machine learning platform. You will tackle the most complex and impactful technical challenges, shaping the architecture and technology choices that enable our ML capabilities to scale and deliver exceptional user experiences. You will be a key influencer, bridging the gap between engineering and product, and a mentor to senior engineers, fostering a culture of technical excellence and continuous improvement. Your work will be used by millions of users.

Responsibilities:

• Design and build scalable, high throughput, and low latency distributed systems using Scala
• Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration
• Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art.
• Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary
• Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc.
• Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi.  

Your Background:

• Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM based language is a plus.
• Strong experience with AWS or an equivalent cloud platform
• Experience building online microservices at scale with low latency serving
• Experience with both SQL (e.g. Postgres) and NoSQL databases (e.g. Cassandra), message brokers (e.g. Kafka), and caches (e.g. Redis)
• Experience with containerization technologies, such as Docker or Kubernetes
• Led the response and resolution efforts for multiple major, large-scale incidents

Bonus:

• Familiarity with the machine learning infrastructure like inference engines (e.g. torschserve, triton, vLLM), vector stores (e.g. LanceDB, FAISS), feature stores (e.g. Feast), ElastiCache, model training orchestration, etc.
• Understanding of ML model training pipelines and model internals. Experience with Recommender Systems, Search, Autocomplete and Ads ML is a plus
• Previous experience with Akka, Erlang, Elixir or Go
• Proficient in data-driven analysis of complex A/B testing results

About Tubi:

Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation.

#LI-Hybrid

By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalized than ever before. Learn more at geniussports.com   

The Role – Senior Software Engineer

We are looking for a senior 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. 
 
What You'll Do 

• 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. 

  
What You’ll Bring:   

• 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. 

 
It’ll be a bonus if you know: 

• 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 

The base salary range for this role is $175,000 - $220,000. This role will also be eligible to take part in Genius Sports Group's benefits plan. 

We enjoy an ‘office-first’ culture and maximize opportunities to collaborate, connect and learn together. Our hybrid working models differ depending on your role and location. Occasional travel may be required. 

As well as a competitive salary and range of benefits, we’re committed to supporting employee wellbeing and helping you grow your skills, experience and career. Learn more about how rewarding life at Genius can be at Reward | Genius Sports.  

One team, being brave, driving change   

We strive to create an inclusive working environment, where everyone feels a sense of belonging and the ability to make a difference. Learn more about our values and culture at Culture | Genius Sports.   

Let us know when you apply if you need any assistance during the recruiting process due to a disability.