Engineering Manager- AI OSS Ecosystem, Singapore

P-1389

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As the Engineering Manager on the AI OSS Ecosystem team, you will work with your team to build and maintain open-source AI/ML Ops platforms that empower users to efficiently train, deploy, and monitor models and GenAI agents at scale. You will also collaborate with the broader AI/ML community to drive advancements in AIOps capabilities across the industry.

The impact you'll have:

• Lead the development of MLflow, one of the industry’s most widely used open-source MLOps platforms.
• Partner with engineering and product leadership to define, shape, and drive the future of Databricks’ AIOps ecosystem.
• Build and scale a world-class team by recruiting top-tier talent, establishing a strong team structure, and fostering effective collaboration with both internal and external stakeholders.
• Establish robust engineering processes to seamlessly execute the product vision, strategy, and roadmap, ensuring alignment with organizational goals and priorities.
• Work with the global AI/ML community to push the boundaries of AIOps innovation.

What we look for:

• BS (or higher) in Computer Science, or a related field
• 5+ years of hands-on experience in building backend systems
• 2+ years leading and managing a high-performing engineering team
• A passion for AI/ML Open-Source tooling and the ability to drive technical initiatives that improve overall team efficiency and code quality
• Demonstrated ability to mentor, coach, and develop top-notch engineering talent at various levels
• Experience in setting and achieving ambitious team goals aligned with company objectives
• Experience managing distributed teams across multiple locations
• Adaptability and resilience in a fast-paced, rapidly evolving tech environment

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, please visit https://www.mybenefitsnow.com/databricks. 

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.