CSQ427R171
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.
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, 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
- Willing to travel once every 4-8 weeks to see customers (as needed)
- Language Proficiency: Native-level fluency in Korean and professional working proficiency in English (both written and verbal).
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At 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.
Compliance
If 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.
Skills Required
- Experience building GenAI applications with tools like HuggingFace and LangChain
- Expertise in deploying production-grade GenAI applications
- Hands-on industry data science experience with tools like PyTorch
- Experience building machine learning deployments on AWS, Azure, or GCP
- Graduate degree in a quantitative discipline or equivalent experience
- Experience communicating technical concepts to various audiences
- [Preferred] Experience using Databricks Intelligence Platform and Apache Spark
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Equity Value & Accessibility — Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
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Healthcare Strength — Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
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Parental & Family Support — Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
