Senior Applied AI Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Mental health support

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Childcare support

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Learning budget

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Senior Applied AI Engineer Belgrade, Serbia 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

Read the full description at databricks.com. FewerJobs shows a preview and links to the original posting.