Senior Applied AI Engineer(m/w/x)

Requirements

• 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

Tasks

• 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.

Work Experience

EducationMore information about education requirement

Languages

Tools & Technologies