Specialist Solutions Architect - Genai / Ml

OverviewAs a Specialist Solutions Architect (SSA) - Data Science & ML, 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.ResponsibilitiesArchitect 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 MLOpsProvide 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 DatabricksCollaborate 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 offeringsBuild and increase customer data science workloads and apply the best MLOps to productionize these workloads across a variety of domainsServe 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 monitoringWhat we look for5+ years of hands-on industry ML experience in at least one of the followingML 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 OpenAIExperience communicating and teaching technical concepts to non-technical and technical audiences alikePassion 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 datasetsCan meet expectations for technical training and role-specific outcomes within 3 months of hireCan travel up to 30% when neededAbout DatabricksAt Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel.

We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards.

Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.ComplianceIf access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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