Specialist Solutions Architect

Summary

Join Databricks as a Specialist Solutions Engineer and become a trusted technical ML advisor for customers and the Field Engineering organization. Collaborate with Solution Architects and senior team members to guide customers in designing production-grade ML applications on the Databricks platform. Align customer technical roadmaps with the evolving Databricks Data Intelligence Platform. Enhance your technical skills by applying the latest technologies in GenAI, MLOps, and ML, and expand your influence through mentorship. Architect production-level ML workloads for customers, provide advanced technical support to Solution Architects, collaborate with product and engineering teams, build and increase customer data science workloads, and serve as a trusted technical advisor for customers developing GenAI solutions.

Requirements

• 3+ years of hands-on professional experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving our values through ML
• Can meet expectations for technical training and role-specific outcomes within 3 months of hire
• Can travel up to 30% when needed

Responsibilities

• Architect production level ML workloads for customers using our unified platform, including end-to-end ML pipelines, training/inference optimization, integration with cloud-native services and MLOps
• Provide advanced technical support to Solution Architects during the technical sale ranging from feature engineering, training, tracking, serving to model monitoring all within a single platform, and participating in the larger ML SME community in Databricks
• Collaborate with the product and engineering teams to represent the voice of the customer, define priorities and influence the product roadmap, helping with the adoption of Databricks’ ML offerings
• Build and increase customer data science workloads and apply the best MLOps to productionize these workloads across a variety of domains
• Serve as the trusted technical advisor for customers developing GenAI solutions, such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, content generation, and monitoring

Preferred Qualifications

• 1+ years customer-facing experience in a pre-sales or post-sales role
• Experience working with Apache Spark™ to process large-scale distributed datasets

Benefits

• Annual performance bonus
• Equity