AI Engineer
CSQ326R35
Mission
The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.
The impact you will have:
Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems
Own production rollouts of consumer and internally facing GenAI applications
Serve as a trusted technical advisor to customers across a variety of domains
Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap
What we look for:
Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
Expertise in deploying production-grade GenAI applications, including evaluation and optimizations
Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
Experience building production-grade machine learning deployments on AWS, Azure, or GCP
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 AI
[Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets
AI Engineer
CSQ326R35
Mission
The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.
The impact you will have:
Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems
Own production rollouts of consumer and internally facing GenAI applications
Serve as a trusted technical advisor to customers across a variety of domains
Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap
What we look for:
Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
Expertise in deploying production-grade GenAI applications, including evaluation and optimizations
Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
Experience building production-grade machine learning deployments on AWS, Azure, or GCP
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 AI
[Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets