Senior Applied AI Engineer

Databricks; United States; À distance; USD 150 000 - 230 000; Plein temps

Résumé du poste

Databricks is seeking a Senior Applied ML/AI Engineer to apply machine learning and optimization algorithms to improve AutoML and other user-facing products. You will work on classification, regression, forecasting, and recommendations across both classical and deep learning models.

You will build features, deploy state-of-the-art models, and shape ML investment directions by collaborating with engineering and product teams, aiming to make Databricks’ products faster and more cost-efficient.

Qualifications

• 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 beyond standard libraries.
• Strong coding and software engineering skills, testing, reviews and deployment.
• Broad mathematical modelling knowledge beyond ML.
• Nice to have: deployment, scaling, monitoring models in production; Tier 0 infra requirements.

Responsabilités

• Build features and run end-to-end systems in a small team of engineers and data scientists.
• Shape the direction of applied ML investments by engaging with engineering and product teams.
• Drive development and deployment of state-of-the-art ML/AI models and systems across Databricks products and infrastructure.
• Architect robust, scalable ML infrastructure including training and serving components for production environments.
• Work on novel ML modeling techniques for forecasting.
• Contribute to the AI community through conferences and open source involvement.

Connaissances

ML engineering

Systems & statistics

Production ML systems

Coding & testing

Mathematical modelling

Deployment & monitoring

Description du poste

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.

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.

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.