AI & Analytics Engineer

ViDA (Varian Intelligence Data Analytics) is the AI and data intelligence platform powering the Siemens Healthineers radiotherapy ecosystem. ViDA ingests real‑time telemetry from linear accelerators (LINACs) deployed in cancer treatment centers around the world — transforming that data into actionable insights for clinical engineers and service teams.

We are seeking an AI & Analytics Engineer who thrives at the intersection of AI engineering, solution architecture, and data platforms. This is a true end‑to‑end role: you will take problems from initial discovery and system design through to production deployment and real‑world adoption. You are comfortable switching contexts — discussing model architectures with data scientists, reviewing API contracts with backend engineers, and explaining predictive alerts to field service managers. You care about production quality, reliability, and impact. The systems you build don’t just live in notebooks — they run inside cancer treatment centers.

What We Offer

• 100% Remote (Spain) or (United Kingdom) - Work from anywhere in Spain or the UK — no relocation, no office mandate

• Real‑World Impact - Your solutions run inside cancer treatment centers. The work — and the stakes — are real.

• AI‑Native Stack - Databricks, Azure, LLMs — modern tooling without legacy constraints

• Global Scale - A Fortune 500 MedTech organization with colleagues across 30+ countries

• Patented Research - Collaborate on cutting‑edge ML for radiotherapy analytics (US 12,572,623 B2)

• High Autonomy - Small team, big ownership. You lead your solutions end to end.

What You’ll Do

• Design and deliver end‑to‑end AI solutions, from problem framing and architecture to deployment, monitoring, and iteration, on our Azure + Databricks medallion platform

• Architect and build LLM‑powered applications, including RAG pipelines, AI agents, structured outputs, and intelligent alerting integrated with LINAC telemetry and fault data

• Develop production‑grade APIs (FastAPI) exposing AI capabilities such as model inference, predictive maintenance scores, and anomaly alerts to clinical dashboards and service tools

• Translate clinical and operational requirements into robust AI system designs, acting as a bridge between domain experts (medical physicists, field engineers) and the engineering team

• Integrate ML models and GenAI components into the ViDA data platform, orchestrating inference pipelines, managing model lifecycle with MLflow, and ensuring reliability at scale

• Build and maintain data pipelines (PySpark, Delta Lake) that provide clean, validated telemetry, dosimetry, and MPC data from the global LINAC fleet

• Own production observability for AI systems, including latency, data drift, and model degradation, driving continuous improvement based on real‑world performance

• Champion AI adoption across internal teams through clear documentation, technical onboarding, and explainable, actionable AI outputs

Technology Stack - Must Have

• Python (production‑grade): FastAPI, Pydantic, async programming

• LLMs in production: RAG, agents, tool use, structured outputs

• Azure cloud services: Container Apps, Blob Storage, Event Hubs, Service Bus

• Databricks, Delta Lake, PySpark

• API design and integration: REST, async, OpenAPI

• SQL and data modelling (fact/dimension models, incremental pipelines)

• ML fundamentals: model integration, inference, validation

Nice to Have

• MLflow (experiment tracking, model registry, serving)

• PostgreSQL and/or MongoDB

• Prompt engineering and LLM evaluation frameworks

• Next.js / React for lightweight AI frontend applications

• dbt, Power BI, or semantic model development

What You Bring

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field — or equivalent practical experience

• Proven experience building AI systems in production, with real users and real‑world consequences

• Strong Python engineering skills, with an emphasis on clean, testable, and maintainable code

• Deep familiarity with LLMs and GenAI patterns, including RAG, agents, structured outputs, function calling, evaluation, and monitoring

• Hands‑on experience with Azure and modern cloud‑native architectures (containerisation, managed services, event‑driven systems)

• Comfort working across the stack — from data pipelines and APIs to stakeholder presentations

• Excellent communication skills, with the ability to tailor explanations for technical and non‑technical audiences

• A proactive, ownership‑driven mindset — you identify problems early and follow through to resolution

• Based in Spain (or holding valid EU work authorization); English required, Spanish is a plus

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Apply now and help us transform cancer care through AI.

Someone, somewhere, will be glad you did.

#LI-REMOTE