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GEGenius Sports

Senior Applied AI Engineer(m/w/x)

Lausanne
Vollzeitmit HomeofficeSenior
AI/ML

Developing audio/visual sensor agents for sports data, building streaming pipelines for structured outputs at a sports tech firm. Hands-on LLM or multimodal model integration experience required. Focus on robust, real-time streaming AI systems for immersive sports experiences.

Anforderungen

  • 5-8+ years professional software engineering experience (backend and/or ML systems)
  • Strong proficiency in Python, Java, or Rust
  • Hands-on experience with LLM or multimodal model integration (Gemini, ChatGPT, Claude)
  • Comfort with ambiguity, iterative experimentation, evidence-based decision-making in Agile
  • Experience with streaming data platforms (Kafka, Pulsar, Flink)
  • Experience with AWS Bedrock or Google Vertex AI
  • Familiarity with version control systems (Git)
  • Excellent problem-solving skills and attention to detail
  • Ability to work independently and in a team
  • Strong communication skills
  • Experience with audio ML / speech / acoustic event detection, or media pipelines
  • Experience with RAG or rules/config grounding for sport-specific logic
  • Familiarity with evaluation practices and production observability
  • Experience operating systems with cost/latency tradeoffs
  • Occasional travel may be required

Aufgaben

  • Develop audio sensor agents for acoustic events, sentiment, and alignment.
  • Develop visual sensor agents for scorebug reading and basic visual cues.
  • Develop specialist and decision logic components for structured outputs, confidence, and traceability.
  • Implement streaming-friendly pipelines with chunking, normalization, time-sync, and async execution.
  • Integrate robust retry and backoff for model/tool calls.
  • Develop prompt-as-code with strict JSON contracts, schema validation, and deterministic post-processing.
  • Design fallback behaviors for degraded modes.
  • Add guardrails and confidence thresholds.
  • Instrument traces and metrics for latency, cost, and accuracy.
  • Partner with leads to translate sport rules and edge cases into validation logic.
  • Integrate system outputs into downstream consumers like tagging, live feeds, and analytics.
  • Enhance evaluation workflow with test cases and failure categories.
  • Implement regression checks for prompts and model routing.
  • Stay updated on emerging Gen AI technologies, tools, and best practices.
  • Mentor and support team members in data engineering principles and practices.

Berufserfahrung

5 - 8 Jahre

Ausbildung

Bachelor-AbschlussODERMaster-Abschluss

Sprachen

Englischverhandlungssicher

Tools & Technologien

PythonJavaRustLLMmultimodal modelGeminiChatGPTClaudeKafkaPulsarFlinkAWS BedrockGoogle Vertex AIGitMLRAG
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Genius Sports erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
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