P-1439
As a Senior Applied ML/AI Engineer at Databricks, you will apply machine learning and optimization algorithms to improve the usability and efficiency of the current AutoML and several other user-facing products that will benefit from better classification, regression, forecasting, and recommendations, either classical or based on deep learning. From statistical models all the way down to deep and foundational models, feature augmentation and auto-tuning, our Applied ML/AI team works on some of the most complex, most interesting problems facing businesses, making Databricks' infrastructure and products as performant and cost-efficient as possible. This is a high-impact problem as our customers look at us to deliver the most out of their data.
The impact you will have:
- Build features and run end-to-end systems in a small team of experienced engineers and data scientists.
- Shape the direction of our applied ML investment by engaging with engineering and product teams across the company.
- Drive the development and deployment of state-of-the-art ML/AI models and systems that directly impact the capabilities and performance of Databricks’ products, infrastructure, and services.
- Architect and implement robust, scalable ML infrastructure, including model training and serving components to support seamless integration of AI/ML models into production environments.
- Work on novel modeling techniques in the field of ML for forecasting.
- Possibilities to contribute to the broader AI community by presenting at conferences and actively participating in open source projects, enhancing Databricks’ reputation as an industry leader.
What we look for:
- 2-8 years of machine learning engineering experience in high-velocity, high-growth companies
- Strong understanding of both computer systems and statistics
- Experience developing AI/ML systems at scale in production
- Strong track record of ML modeling that goes beyond using standard libraries.
- Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews, and deployment.
- A large breadth of knowledge or willingness to develop mathematical modelling beyond the ML.
- Nice to have: experience deploying, scaling, and monitoring models in production; understanding of the unique infrastructure challenges posed by training and serving predictions in Tier 0 environments.
Why Join Us?
At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.
If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you!
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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
- 2-8 years of machine learning engineering experience
- Strong understanding of computer systems and statistics
- Experience developing AI/ML systems at scale in production
- Strong record of ML modeling beyond standard libraries
- Strong coding and software engineering skills
- Willingness to develop in mathematical modeling beyond ML
- Nice to have experience deploying, scaling and monitoring models
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 are a meaningful part of offers, and periodic tender opportunities and secondary options have made private equity more tangible for many employees. This perceived upside contributes to strong total-compensation sentiment in key roles.
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Healthcare Strength — Comprehensive medical, dental, and vision coverage is paired with mental‑health resources and wellness reimbursements, indicating a robust health package. Multiple summaries highlight broad coverage that employees can practically use.
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Leave & Time Off Breadth — Generous PTO, paid holidays/sick time, and fully paid parental leave are frequently described, with hybrid/remote flexibility common in the U.S. These policies expand time‑off accessibility across different life stages.
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.
