The Machine Learning (ML) Practice team is a highly specialized, customer-facing ML team at Databricks, facing an increasing demand for Large Language Model (LLM)-based solutions. We deliver professional services engagements to help our customers build, scale, and optimize ML pipelines, as well as deploy these pipelines in production. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations teams, 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 enhance the overall strength of the team. This team is the right fit for you if you love working with customers, collaborating with teammates, and fueling your curiosity for the latest trends in LLMs, MLOps, and ML more broadly. 

The impact you will have:

• Develop an ML Center of Excellent (CoE) in APJ for Professional Services 
• Develop LLM solutions on customer data, such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation
• Build, scale, and optimize customer data science workloads, applying best-in-class MLOps to productionize these workloads across a variety of domains
• Advise data teams on various data science such as architecture, tooling, and best practices
• Scope engagements and oversee/upskill team members and partners delivering on engagements
• Present at conferences such as Data+AI Summit and Executive Briefings (EBCs)
• Provide technical mentorship to the broader ML SME community within Databricks
• Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap, ensuring APJ’s specific ML needs are captured

What we look for:

• Experience with the latest techniques in natural language processing including, vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI
• 6+ years of hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and PyTorch/TensorFlow
• 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 both non-technical and technical audiences 
• Passion for collaboration, life-long learning, and driving business value through ML
• [Preferred] Experience working with Apache Spark to process large-scale distributed datasets

Benefits

• Private medical, dental and optical
• Life, accident, disability and critical illness coverage
• Central Provident Fund for local nationals
• Equity awards
• Enhanced Parental Leaves
• Fitness reimbursement
• Annual career development fund
• Home office & work headphones reimbursement
• Business travel accident insurance
• Mental wellness resources
• Employee referral bonus

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.

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.