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Senior Software Engineer, Sports AI

Genius Sports Ltd - Los Angeles, California, United States

Posted Feb 5, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Verification
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Salary
$160K-$230K Verified - from the job posting source checked Jun 20, 2026
401(k) match
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Market context

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

67% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type
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Weekend work
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Company

Company stage
Public-company Verified - from the job posting source checked Jun 20, 2026

Application

Cover letter
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Assessment
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Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior Software Engineer, Sports AI Los Angeles, California, United States 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 . About the Role 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

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