onsite
Specialist Solutions Architect (GenAI)
Specialist Solutions Architect (GenAI)
The Specialist Solutions Architect (GenAI) at Databricks will act as a trusted ML expert, guiding customers in architecting production-grade ML applications, especially those leveraging GenAI, on the Databricks Data Intelligence Platform. This role involves building, scaling, and optimizing customer data science workloads, applying MLOps best practices, and influencing product roadmaps based on customer feedback.
About the role
About the Role
As a Specialist Solutions Architect (SSA) - Data Scientist / ML Engineer, you will serve as the trusted technical ML expert for both Databricks customers and the Field Engineering organization. You will collaborate with Solution Architects to guide customers in architecting production-grade ML applications on Databricks, aligning their technical roadmap with the evolving Databricks Data Intelligence Platform. This role offers the opportunity to strengthen your technical skills by applying cutting-edge technologies in GenAI, MLOps, and broader ML, while expanding your impact through mentorship and establishing yourself as an ML thought leader. You will report to the Manager, Field Engineering.
The Impact You Will Have
- Architect production-level ML workloads for customers using our unified platform, encompassing 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, covering aspects from feature engineering, training, tracking, serving to model monitoring, all within a single platform, and participate in the larger ML SME community at Databricks.
- Collaborate cross-functionally with product and engineering teams to represent the voice of the customer, define priorities, and influence the product roadmap, thereby aiding the adoption of Databricks' ML offerings.
- Build, scale, and optimize customer data science workloads and apply best-in-class MLOps to productionize these workloads across diverse domains.
- Serve as the trusted technical advisor for customers developing GenAI solutions, including RAG architectures on enterprise knowledge repositories, 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 areas:
- ML Engineer: Building and maintaining production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.
- Data 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/or teaching technical concepts to non-technical and technical audiences alike.
- Passion for collaboration, life-long learning, and driving business value 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.
- Ability to meet expectations for technical training and role-specific outcomes within 3 months of hire.
Benefits
- Private medical, dental and optical
- Life, accident, disability and critical illness coverage
- Central Provident Fund for local nationals
- Equity awards
- Enhanced Parental Leaves
- Fitness reimbursement
- Annual career development fund
- Home office & work headphones reimbursement
- Business travel accident insurance
- Mental wellness resources
- Employee referral bonus