Senior AI Engineer, Multimodal Real-Time Signals

Senior Applied AI Engineer – Multimodal Systems
Location: Lausanne, Switzerland (Hybrid) – Competitive Salary

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About the Company

We are a fast‑growing sports‑technology leader based in Lausanne, dedicated to turning raw event data into actionable insights for athletes, teams, and fans worldwide. Our platform fuses audio, video, and textual streams to power real‑time analytics, automated highlights, and next‑generation fan experiences.

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Role Overview

As a Senior Applied AI Engineer, you will own the design, development, and deployment of production‑grade multimodal pipelines that ingest and process audio, video, and text. You’ll work hand‑in‑hand with product managers, domain experts, and data scientists to refine our event‑detection engines, ensuring they are robust, scalable, and ready for real‑world use.

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Key Responsibilities

Area	What You’ll Do
Algorithm Development	Design and implement state‑of‑the‑art multimodal models (e.g., audio‑visual event detection, speech‑to‑text, video summarisation).
Production Engineering	Build end‑to‑end pipelines (data ingestion → preprocessing → inference → post‑processing) that run reliably at scale on cloud or edge environments.
Collaboration	Partner with product leads to translate user requirements into technical specifications; work with domain experts to fine‑tune detection thresholds and labeling strategies.
Performance & Reliability	Establish monitoring, logging, and automated testing frameworks; continuously improve latency, throughput, and model accuracy.
Research & Innovation	Stay current with the latest AI research (transformers, multimodal fusion, self‑supervised learning) and evaluate their applicability to our product roadmap.
Mentorship	Guide junior engineers, conduct code reviews, and champion best practices in software engineering and AI development.

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Required Experience & Skills

Must‑Have	Preferred
5+ years of professional software engineering experience.	Experience in Rust for performance‑critical components.
Strong proficiency in Python (including libraries such as PyTorch, TensorFlow, OpenCV, librosa).	Proven track record with Java in large‑scale backend services.
Hands‑on experience building multimodal AI systems (audio, video, text).	Prior work in the sports, media, or entertainment domain.
Production‑level knowledge of CI/CD, containerisation (Docker/Kubernetes), and cloud platforms (AWS, GCP, Azure).	Familiarity with edge deployment (e.g., NVIDIA Jetson, Coral).
Ability to write clean, maintainable, and well‑documented code.	Publications or open‑source contributions in multimodal AI.
Excellent problem‑solving skills and a data‑driven mindset.	Experience with MLOps tools (MLflow, Kubeflow, Seldon).
Strong communication and teamwork abilities.	Knowledge of real‑time streaming frameworks (Kafka, Pulsar, gRPC).

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What We Offer

• Competitive salary + performance bonuses.
• Hybrid work model – 3 days a week in our modern Lausanne office, 2 days remote.
• Generous relocation assistance (if applicable).
• Health & wellness benefits, including private health insurance and a fitness stipend.
• Continuous learning budget for conferences, courses, and certifications.
• A collaborative, high‑impact environment where your work directly shapes the future of sports analytics.

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How to Apply

Send your CV, a brief cover letter highlighting relevant projects (especially any multimodal AI work), and links to any public code repositories or publications to careers@sportstech-lausanne.com with the subject line “Senior Applied AI Engineer – J-18808-Ljbffr.”

We look forward to seeing how you can help us turn raw sports data into the next generation of intelligent experiences!