Sr. Solutions Engineer AI/ML

Databricks is seeking a Senior Solutions Engineer specializing in AI/ML to join their team in Munich, Germany. This role combines technical expertise in machine learning with customer-facing responsibilities, making it an ideal position for those who want to impact how organizations implement AI solutions.

The role involves working directly with clients to demonstrate and implement Databricks' Data Intelligence Platform, focusing on advanced AI/ML solutions including GenAI architectures, RAG implementations, and MLOps practices. You'll be responsible for building relationships with clients throughout your assigned territory, collaborating with Account Executives and Senior Solutions Architects to deliver technical and business value.

As a Solutions Engineer, you'll serve as an ML/AI expert, helping customers develop and implement various AI solutions including RAG architectures on enterprise knowledge repositories, natural language querying of structured data, content generation, and monitoring systems. The role requires both technical depth in ML/AI and the ability to communicate complex technical concepts to diverse audiences.

The ideal candidate brings 3+ years of hands-on ML industry experience, strong programming skills in languages like Python or Java, and experience with cloud platforms (AWS/Azure/GCP). You should be comfortable with modern ML technologies including vector databases, LLMs, and MLOps practices. Experience with tools like HuggingFace, Langchain, and OpenAI is valuable.

At Databricks, you'll be part of a company that values innovation and customer success, working with a collaborative team that's helping organizations worldwide transform their businesses through data and AI. The company offers comprehensive benefits and is committed to fostering a diverse and inclusive culture where everyone can excel.

This role offers significant growth opportunities, with a clear path toward becoming an independently operating Solutions Architect. You'll have the chance to influence product development by representing the voice of the customer to product and engineering teams, helping shape the future of Databricks' ML offerings.