Skip to content
NEXTMOVEFDE careers · United States

AI Engineer - FDE (Forward Deployed Engineer)

About Databricks

Unified Data Intelligence Platform (lakehouse + Mosaic AI) used by 10,000+ orgs and 50%+ of the Fortune 500 for ETL, BI, ML, and GenAI.

Private Late

Job description

The full responsibilities and requirements are on the employer’s site.

Read the job description
Source and classification

Production engineering · Evidence for this classification:

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. This role is intended for experienced
More from the 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. This role is intended for experienced engineers with demonstrated industry experience designing, building, and deploying production GenAI and LLM applications at scale. It is not intended for internship, new graduate, or entry-level applicants. 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 va [... source excerpt omitted ...] xperience 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/ [... source excerpt omitted ...] AI [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets Willing to travel once every 4-8 weeks to see customers (as needed) Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected 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 locatio

How jobs are selected

Employer postings · Data from · Sources