AI​/ML Engineer

The Future of Marketing Starts Here Entirely is the first open Martech ecosystem to enable Tailored Marketing  mission is to build a whole world of marketing technology, powerfully personalized and finely calibrated, irely lays the foundation for hyper-personalized marketing by connecting and orchestrating existing marketing technologies while preserving and enhancing customers’ current Martech investments. Founded by Marmind, Censhare, Elaine, and Facelift, Entirely today serves more than 2,800 clients across twelve countries, with a team of over 400 professionals.

It is more than a product or platform. It is a open ecosystem and a catalyst for marketing that matters.

Entirely is creating the first AI-native operating system for marketing — a platform that allows enterprise teams to orchestrate campaigns, channels and content with unprecedented automation, personalization and control. Headquartered in Switzerland, we work with portfolio companies, strategic technology partners and leading academic institutions to address one of the biggest challenges in enterprise tech today: the fragmentation and complexity of the marketing stack.

Join our dedicated hub for AI innovation, where bold ideas are tested, breakthrough capabilities are developed and emerging research is translated into enterprise-ready solutions. In close collaboration with core business units and universities such as ETH Zurich, we move from rapid prototypes to production pilots that redefine how global marketing teams operate.

We are actively hiring AI/ML Engineers who want to work hands-on at the frontier of agentic AI. You will design, train and deploy machine learning models, build robust data pipelines, and contribute to the orchestration layer that powers our marketing agents. You will collaborate with product, design and research colleagues to turn prototypes into enterprise-grade applications.

You will operate at the intersection of research and product: experimenting with LLMs and multimodal models, optimizing ML workflows, and ensuring deployed systems are scalable, efficient and compliant. This is an opportunity to be part of a small, high-caliber team, working end-to-end on problems that combine cutting-edge AI with real-world business impact.

Location
:
Hybrid (Zug & Zurich, Switzerland)
Seniority
:
Mid / Senior
Start
:
As soon as possible

• Design, train/tune and deploy ML models for NLP, classification, recommendation and orchestration tasks.
• Build and optimize data pipelines for collection, preprocessing, training, evaluation and deployment.
• Contribute to the development of a Python-based agent runtime (e.g. Google ADK execution environment) and ensure seamless integration with enterprise systems.
• Establish and apply MLOps practices: model lifecycle management, experiment tracking, automated testing, monitoring.
• Collaborate closely with full-stack engineers, product managers and designers to turn prototypes into enterprise-ready applications.
• Act as an internal dogfooder and early adopter of no-code/low-code automation (Zapier, n8n, Make) and AI assistants (ChatGPT, MS Copilot Studio). Build lightweight agents, workflow automations and internal tools to mirror how marketing technologists will use the platform.
• Participate actively in design discussions and help shape technical decisions for the stack in a growing startup environment.

• Bachelor’s, Master’s or PhD in Computer Science, AI/ML, Data Science or a related field (or equivalent practical experience).
• Strong proficiency in Python, with experience in ML frameworks (PyTorch, Tensor Flow, Hugging Face Transformers).
• Familiarity with backend development (APIs, SDKs, microservices); bonus if comfortable with React/Type Script but not required.
• Experience with cloud infrastructure (AWS preferred), containerization (Docker, Kubernetes) and CI/CD pipelines.
• Hands-on experience with MLOps tooling (MLflow, Weights & Biases or similar).
• Exposure to agentic AI frameworks (Lang Chain, Autogen, Lang Graph) and willingness to deepen skills quickly.
• Curiosity about workflow automation platforms (e.g. Zapier, n8n, Make) and ability to prototype AI-driven assistants.
• Startup…