Senior Machine Learning Engineer (f/m/d)
Tech Stack
Agent Workflow
Build real-world AI/ML solutions for Contentful's content management platform used by thousands of enterprise customers. Deploy LLM-based models for NLP tasks, optimize generative AI products, implement RAG and Agent Architectures for content management use cases.
About the Role
About the Opportunity
Become part of the AI revolution at Contentful where we build real world AI solutions for thousands of active customers.
At Contentful you will help imagine, drive, and build ML solutions which produce immediate customer impact by helping them get more done than they ever imagined. We are looking for an excellent machine learning engineer who understands and has experience in this field and current Generative AI trends. If you're passionate about pushing the boundaries of what's achievable with ML products on a large scale content management system, we want you on our team.
What to expect?
- Measure and ensure the high-quality output of ML workloads for our enterprise customers.
- Design, build, and measure production software in the Contentful Platform.
- Conduct focused research and testing using tools like Jupyter Notebook.
- Optimize generative AI products for accuracy, speed, and scalability.
- Integrate ML cloud solutions and adapt them to our large-scale use cases.
- Integrate prompt engineering and fine-tuning for customer use cases.
- Develop software that scales to meet the demands of high-load customer workloads.
- Lead design reviews with peers and stakeholders to decide amongst available technologies.
- Drive the ML education in the team and establish a high standard of quality & ownership
What you need to be successful?
- Proven experience as a technical leader in a product software development environment
- Proven Track Record in Model Development, including successfully developing and deploying LLM-based models for various NLP tasks in real-world applications with production workloads
- Proven ability to work backwards from customer needs to deliver ML-based features that meet those needs
- Familiarity with distributed systems and cloud services (e.g., AWS, Azure, GCP)
- Solid understanding of machine learning principles
- Experience with container frameworks such as Docker or Kubernetes
- Up-To-Date on The Latest Updates on LLM Development & Research: From RAGs to Open-Source models over Agent Architectures – you have an inherent drive to stay up-to-date on what is the latest and greatest