Databricks
Data and AI
AIEngineer-FDE(ForwardDeployedEngineer)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“AI Engineer - FDE (Forward Deployed Engineer) at Databricks. Skills: AI Engineering, Forward Deployed Engineering, GenAI, LLMOps, Machine Learning. Build and productionize first-of-its-kind AI applications. Develop cutting-edge GenAI solutions”
What You'll Achieve.
Build and productionize first-of-its-kind AI applications; Solve customer problems; Own production rollouts of consumer and internally facing GenAI applications; Influence priorities and shape the product roadmap
Industry & Context.
Solve customer problems
Willing to travel once every 4-8 weeks to see customers (as needed)
What They're Looking For.
Must Have
Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., 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
Nice to Have
Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets
What You'll Do.
Build and productionize first-of-its-kind AI applications
Develop cutting-edge GenAI solutions
Incorporate the latest techniques from Databricks AI research to solve customer problems
Own production rollouts of consumer and internally facing GenAI applications
Serve as a trusted technical advisor to customers
Present at conferences
Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap
How You'll Work.
Team & Collaboration
Work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations; Support internal subject matter expert (SME) teams; Work with teammates; Collaborate cross-functionally with the product and engineering teams
Communication Scope
Communicating and/or teaching technical concepts to non-technical and technical audiences alike
Full Job Description
AI Engineer - FDE (Forward Deployed Engineer) (ALL LEVELS) CSQ327R177 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. Open to remote locations. The impact you will have: Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks 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, Stat
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