Senior Applied AI Engineer

Databricks; San Francisco (CA); On-site; USD 166,000 - 211,000; Full time

Job summary

As a Senior Applied AI Engineer at Databricks, you'll enhance our engineering systems through advanced machine learning and optimization. You'll collaborate with a skilled team to innovate AI capabilities and drive impactful results, contributing to industry-leading solutions in data and AI.

Qualifications

• 2-8 years of machine learning engineering experience in high-growth companies.
• Strong understanding of systems and statistics.
• Experience developing AI/ML systems at scale in production.

Responsibilities

• Build end-to-end systems with a team.
• Drive the deployment of AI models impacting Databricks’ products.
• Architect robust ML infrastructure for production environments.

Skills

Machine Learning

Computer Systems

Statistical Analysis

Software Engineering

Model Deployment

Coding

Education

Bachelor's or Master's in Computer Science or related field

Job description

P-1380

As a Senior Applied AI Engineer at Databricks, you will apply machine learning, scheduling and optimization algorithms to improve the efficiency and performance of our engineering systems and infrastructure. From cluster management all the way down to query compilation, our Applied AI team works on some of the hardest, most interesting problems facing the business, 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 optimized workloads.

The impact you will have:

• Build end-to-end systems from the ground up in a small team of experienced people.
• Shape the direction of our applied ML areas of investment by engaging with engineering and product teams across the company.
• Drive the development and deployment of state-of-the-art 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 data storage and processing, model training and serving components, and monitoring and reporting systems to support seamless integration of AI/ML models into production environments.
• Work on novel modeling techniques in the field of ML for Systems
• Contribute to the broader AI community by publishing research, 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
• Large breadth of knowledge or interest in mathematical modeling beyond ML (OR, combinatorial optimization
• 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.
• Experience deploying, scaling and monitoring models in production; deep 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!

Please note we are open to employees working from our Mountain View, CA office for this position.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base 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 location. Based on the factors above, Databricks utilizes the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range

$166,000—$210,250 USD

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 onTwitter,LinkedInandFacebook.

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 visithttps://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.