Specialist Solutions Architect - GenAI & LLMs

FEQ425R89

This role can be remote.

As a Specialist Solutions Architect (SSA) - ML Engineering, you will be the trusted technical ML expert to both Databricks customers and the Field Engineering organization.

You will work with Solution Architects to guide customers in architecting production-grade ML applications on Databricks, while aligning their technical roadmap with the evolving Databricks Data Intelligence Platform.

You will continue to strengthen your technical skills through applying the latest technologies in GenAI, LLMOps, and ML, while expanding your impact through mentorship and establishing yourself as a ML expert.

The impact you will have :

• 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

What we look for :

• 5+ years of hands-on industry ML experience in at least one of the following : ML Engineer : Develop production-grade cloud (AWS / Azure / GCP) infrastructure that supports the deployment of ML applications, including drift monitoringData Scientist : 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 and teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving our values through ML
• Preferred 2+ years customer-facing experience in a pre-sales or post-sales role
• Preferred Experience working with Apache Spark™ to process large-scale distributed datasets
• Can meet expectations for technical training and role-specific outcomes within 3 months of hire
• Can travel up to 30% when needed

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range for this role is listed below and represents base salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks utilizes the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

Canada Pay Range$132,000 $233,500 CAD