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Senior Applied AI Engineer

Genius SportsLausanne, Vaud, Switzerland
On-site Full-time

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Experience Level

Senior

Qualifications

The ideal candidate will have extensive experience in AI engineering, with a focus on multimodal systems. Proficiency in machine learning frameworks, data processing, and software development practices is essential. Strong problem-solving skills, effective communication, and a collaborative mindset are crucial for success in this role. Familiarity with Agile methodologies and a commitment to continuous improvement are also important.

About the job

 

 

At Genius Sports, we’re revolutionizing the sports experience for fans around the globe by leveraging cutting-edge technology and unparalleled live data, delivering immersive, interactive, and personalized experiences like never before. Discover more at geniussports.com.

About the Role  

We are seeking a skilled Senior Applied AI Engineer to develop production-grade, multimodal systems (audio/video/text) that transform broadcast and radio feeds into structured, real-time signals and event candidates. You will play a pivotal role in implementing and enhancing “agentic” components, such as sensor agents and decision logic, which power innovative products like Audio Intelligence, semi-automated broadcast-to-data tagging, and highlight/momentum signals.

Your technical expertise and pragmatic problem-solving approach will be essential as you collaborate within a team that values Agile delivery principles and continuous improvement. You will adopt a data-driven mindset, embracing the principles of continuous experimentation and validation.

Key Responsibilities 

  • Develop and maintain multimodal agents:
    • Audio sensor agents (acoustic events, sentiment analysis, alignment)
    • Visual sensor agents (scorebug/overlay interpretation, basic visual cues)
    • Specialist and decision logic components (structured event outputs, confidence scoring, traceability)
  • Implement streaming-friendly pipelines encompassing chunking, normalization, time synchronization, asynchronous execution, and robust retry/backoff strategies for model/tool calls.
  • Develop prompt-as-code with strict JSON contracts, schema validation, and deterministic post-processing to enhance system stability.
  • Enhance system resilience against noisy inputs by:
    • Designing fallback behaviors for degraded modes
    • Incorporating guardrails and confidence thresholds
    • Instrumenting traces and metrics for latency, cost, and accuracy
  • Collaborate with product, platform, and domain leads to translate sports rules and edge cases into validation logic and integrate outputs into downstream consumers (tagging, live feeds, analytics).
  • Contribute to the evaluation workflow by adding test cases, failure mode categories, and regression checks for prompts and model routing.
  • Stay updated with emerging generative AI technologies, tools, and trends.

About Genius Sports

Genius Sports is a pioneering technology company transforming the sports industry by delivering innovative data-driven solutions that enhance the fan experience. Our commitment to excellence and continuous evolution sets us apart in the competitive landscape of sports technology.

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