Databricks

CSQ227R13
<h2>Applied AI Engineer, Learning Intelligence</h2>
About the Role
We are building the intelligence layer that powers how learners grow. This role sits at the intersection of machine learning, knowledge representation, and product engineering. You will own the skill and concept graph that defines what learners know and can do, infer skill gaps from behavioral and profile signals, and translate those inferences into personalized recommendations and dynamic learning that guide each learner to their next best step. You will also be the bridge between our AI capabilities and the engineers building our frontend, making sure AI-driven features ship in a way that is explainable, reliable, and production-ready.
What You Will Do
<ul>
<li>Design, build, and maintain a skill and concept graph that maps relationships between skills, roles, domains, and learning content</li>
<li>Develop ML models that infer learner skill levels from usage patterns, work output, assessments, and profile data (not just self-reported input)</li>
<li>Build and iterate on recommendation systems that surface the next best module, suggest learning paths, and generate content dynamically</li>
<li>Partner with frontend engineers to ensure AI outputs are consumed correctly, surfaced with appropriate context</li>
<li>Define explainability standards for model outputs so users and stakeholders understand why a recommendation was made</li>
<li>Collaborate with product and content teams to validate recommendation quality and close feedback loops</li>
<li>Monitor model performance in production and own the evaluation framework for recommendation quality</li>
</ul>
What We Are Looking For
<ul>
<li>5+ years of experience in applied ML or data science, with production recommendation or personalization systems in your background</li>
<li>Hands-on experience with knowledge graphs, graph databases, or ontology design</li>
<li>Experience with LLM APIs and prompt engineering for generative features</li>
<li>Hands-on history of shipping LLM-based systems to production, including large-scale deployment, evaluation frameworks, and agentic workflows</li>
<li>Advanced Python proficiency and experience architecting robust, production-grade applications</li>
<li>Deep familiarity with the modern AI stack, from retrieval and agent frameworks to complex prompt engineering, model evaluation, and context engineering</li>
<li>A high degree of intellectual curiosity and the ability to find elegant, straightforward solutions</li>
<li>Exceptional communication skills, with the ability to translate technical logic for varied stakeholders</li>
</ul><div><div><div> 
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected 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 anticipated utilizing 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 <a href="https://www.databricks.com/sites/default/files/2024-08/us-pay-zone-mapping.pdf" rel="noopener noreferrer ugc" target="_blank">here</a>. 
 </div><div>Zone 1 Pay Range</div><div>$139,000—$191,050 USD</div></div><div><div>Zone 2 Pay Range</div><div>$125,000—$171,950 USD</div></div><div><div>Zone 3 Pay Range</div><div>$118,100—$162,350 USD</div></div><div><div>Zone 4 Pay Range</div><div>$111,200—$152,900 USD</div></div></div><div>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 <a href="https://twitter.com/databricks" target="_blank" rel="noopener noreferrer ugc">Twitter</a>, <a href="https://www.linkedin.com/company/databricks" target="_blank" rel="noopener noreferrer ugc">LinkedIn</a> and <a href="https://www.facebook.com/databricksinc" target="_blank" rel="noopener noreferrer ugc">Facebook</a>. 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 <a href="https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing" rel="noopener noreferrer ugc" target="_blank">here</a>. 
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.</div>

Applied AI Engineer, Learning Intelligence

<h2>Staff Machine Learning Engineer, CustomerLake (ML/LLM)</h2>
RDQ427R109
 
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best Data Intelligence Platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
 
As one of the first engineers in the NYC Engineering office, you'll join a small, nimble team building new products from the ground up. We're building CustomerLake, the Customer Data Platform on Databricks, to bring enterprise-grade ML and AI personalization to every company whose data already lives on Databricks. The best B2C and B2B brands have historically relied on in-house ML/AI teams to power personalization, recommendations, churn and lifetime-value modeling, and audience targeting. Our goal is to deliver that same capability to companies that don't have an in-house team but already have their data in order on Databricks. This is a true 0-to-1 environment, combining the excitement of a startup with the resources of a tech leader like Databricks.
 
The impact you'll have:
<ul>
<li>Evaluate ML and LLM approaches for CustomerLake's personalization use cases, push the models and algorithms forward, and continuously improve quality over time</li>
<li>Go deep on how models behave in production: inspect individual traces, understand how the models reason, and tune and improve from there</li>
<li>Build the platform and evaluation framework that let CustomerLake customers optimize for real business value such as purchases, retention, and product usage, not vanity metrics like email opens and clicks</li>
<li>Push the team toward new directions and novel methods worth tackling, not just optimizing what already exists</li>
<li>Partner closely with product management, engineering, and design to turn ambiguous customer problems into scalable, trustworthy solutions</li>
<li>Set the technical foundation and best practices for our ML/AI personalization work as we grow this into several roles across our products over the next 1-2 years</li>
</ul>
 
What we look for:
<ul>
<li>10+ years of engineering experience, with a strong foundation across the full loop of shipping and improving ML/AI products</li>
<li>Hands-on experience building and evaluating ML models and/or LLM systems for real product or business use cases; your understanding is practical, not purely academic, and you can make models work well inside a product</li>
<li>Experience with personalization based on customer behavior (ideal) or transactions (acceptable), such as recommendations, targeting, churn, or lifetime-value modeling</li>
<li>Proficiency in Python and modern ML frameworks (e.g., PyTorch), with hands-on experience in model evaluation and monitoring AI quality in production</li>
<li>Familiarity with LLMs and generative AI, including techniques like retrieval-augmented generation (RAG), prompt design, fine-tuning, and evaluation</li>
<li>A demonstrated product mindset, with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback</li>
<li>High ownership and bias for action in 0-to-1 environments: comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption</li>
</ul>
 
Nice to have:
<ul>
<li>Experience in martech, ideally a go-to-market or business use case with an analytical (rather than purely transactional) angle</li>
<li>An academic or research background that can help us innovate and develop novel methods</li>
</ul>
 <div><div><div> 
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected 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 anticipates utilizing 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 <a href="https://www.databricks.com/sites/default/files/2024-08/us-pay-zone-mapping.pdf" rel="noopener noreferrer ugc" target="_blank">here</a>. 
 </div><div>Local Pay Range</div><div>$192,000—$260,000 USD</div></div></div><div>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 <a href="https://twitter.com/databricks" target="_blank" rel="noopener noreferrer ugc">Twitter</a>, <a href="https://www.linkedin.com/company/databricks" target="_blank" rel="noopener noreferrer ugc">LinkedIn</a> and <a href="https://www.facebook.com/databricksinc" target="_blank" rel="noopener noreferrer ugc">Facebook</a>. 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 <a href="https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing" rel="noopener noreferrer ugc" target="_blank">here</a>. 
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.</div>

Staff Software Engineer - AI/ML

P-1477
Databricks is transforming how it builds and operates People Technology — moving from traditional SaaS configuration toward an AI-native, agentic stack. You'll be the technical anchor of the People Tech pod, driving the architectural shift from workflow automation to autonomous, multi-agent systems that power HR, recruiting, workforce analytics, and employee experience at scale. This is a rare opportunity to reimagine a critical enterprise domain from the ground up using the very data and AI platform Databricks sells to the world.
What you'll do
<ul>
<li>Architect and build agentic systems that automate and augment People Tech workflows — onboarding, offboarding, comp analysis, policy Q&amp;A, HR service delivery — using LLM orchestration frameworks (LangGraph, AutoGen, or equivalent).</li>
<li>Define the agentic platform strategy for the pod: agent design patterns, tool-calling conventions, retrieval-augmented pipelines, evaluation frameworks, and human-in-the-loop guardrails.</li>
<li>Integrate People Tech systems (Workday, Greenhouse, ADP etc.) as agent-accessible tools and data sources via Databricks Unity Catalog and MCP-style interfaces.</li>
<li>Set the technical bar for the pod — reviewing designs, establishing engineering standards, and leading architectural reviews across the People Tech roadmap.</li>
<li>Influence peers and stakeholders: translate agentic capability into business outcomes for People, Legal, and Finance partners, and mentor engineers in the pod on AI-first thinking.</li>
</ul>
What we're looking for
<ul>
<li>8+ years of software engineering experience, with at least 2 years building production LLM or agentic applications (agents, RAG pipelines, tool-use, multi-agent orchestration).</li>
<li>Deep fluency in Python and experience with agentic frameworks — LangChain/LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.</li>
<li>Strong command of enterprise integration patterns: REST/GraphQL APIs, event-driven architecture, and connecting SaaS HR/HCM platforms programmatically.</li>
<li>Experience with data platforms — Databricks, Spark, or equivalent — and building AI applications on top of lakehouse or warehouse architectures.</li>
<li>Track record as a technical lead: driving architectural decisions, writing RFCs, and raising the quality bar across a team without relying on management authority.</li>
</ul>
Nice to have
<ul>
<li>Prior experience in People Tech, HR tech, or internal tooling domains.</li>
<li>Familiarity with Workday, Greenhouse or similar enterprise HR platforms — especially via API or integration layer.</li>
<li>Experience evaluating and red-teaming LLM agents for safety, reliability, and correctness in sensitive business contexts.</li>
</ul><div><div><div> 
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected 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 anticipates utilizing 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 <a href="https://www.databricks.com/sites/default/files/2024-08/us-pay-zone-mapping.pdf" rel="noopener noreferrer ugc" target="_blank">here</a>. 
 </div><div>Local Pay Range</div><div>$192,000—$260,000 USD</div></div></div><div>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 <a href="https://twitter.com/databricks" target="_blank" rel="noopener noreferrer ugc">Twitter</a>, <a href="https://www.linkedin.com/company/databricks" target="_blank" rel="noopener noreferrer ugc">LinkedIn</a> and <a href="https://www.facebook.com/databricksinc" target="_blank" rel="noopener noreferrer ugc">Facebook</a>. 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 <a href="https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing" rel="noopener noreferrer ugc" target="_blank">here</a>. 
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.</div>

Staff Fullstack Engineer, Agentic Applications

P-1408
The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. 
As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale.
 
Key Responsibilities
<ul>
<li>Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. </li>
<li>Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. </li>
<li>Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. </li>
<li>Contribute to building a robust framework for evaluating search ranking improvements - both offline and online.</li>
</ul>
 
What We’re Looking For
<ul>
<li>BS+ (M.S. or PhD preferred) in Computer Science, or a related field.</li>
<li>10+ years experience developing search relevance systems at scale in production or in high-impact research environments.</li>
<li>Experience applying LLM to search relevance</li>
<li>Experience in one or more of the following:  </li>
<ul>
<li>Query understanding</li>
<li>NLP</li>
<li>Text mining</li>
<li>Recommendations</li>
<li>Personalization</li>
<li>Discovery</li>
<li>Conversational AI </li>
</ul>
<li>Strong understanding of computer science fundamentals.</li>
<li>Contributions to well-used open-source projects. </li>
</ul>
 
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!<div>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 <a href="https://twitter.com/databricks" target="_blank" rel="noopener noreferrer ugc">Twitter</a>, <a href="https://www.linkedin.com/company/databricks" target="_blank" rel="noopener noreferrer ugc">LinkedIn</a> and <a href="https://www.facebook.com/databricksinc" target="_blank" rel="noopener noreferrer ugc">Facebook</a>. 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 <a href="https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing" rel="noopener noreferrer ugc" target="_blank">here</a>. 
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.</div>

Staff Software Engineer  (Search Ranking)

P-1408
The Mission
We are democratizing Data and AI for every enterprise user. Our vision is a world where anyone can master their organization’s data through Apps and AI Agents. We are building the retrieval backbone for two worlds: the high-precision context layer for AI agents and the intuitive search experience for people goal is the same: instant, accurate, and actionable insight.
 
The Role: 
<ul>
<li>As a Search Quality Engineer, you sit at the heart of this transformation. You aren't just building a search engine; you are building the contextual backbone of the entire company.</li>
<li>You will own the quality of results for two distinct but deeply connected "users":</li>
<li>The AI Agent: Optimizing the retrieval layer that allows LLMs to reason over data they weren’t trained on, ensuring they have the "ground truth" needed  to synthesize accurate, high-stakes business actions.</li>
<li>The Human User: Improving the traditional search experience so employees can find assets and answers through intuitive, high-recall interfaces.</li>
</ul>
The Technical Challenge
This isn't a solved problem. You will be tackling "Search" in its most evolved form:
<ul>
<li>Hybrid Retrieval: Balancing traditional keyword-based search (for exactness) with semantic vector search (for intent).</li>
<li>Dual-Optimization: Fine-tuning ranking models that satisfy both human readability and LLM-ready context.</li>
<li>High-Stakes Accuracy: In a world of Agents, poor search quality leads to hallucinations. You will build the guardrails and relevance scoring that ensure our AI stays grounded in reality.</li>
<li>Data Heterogeneity: Connecting the dots across structured SQL tables, unstructured docs, and real-time business metrics.</li>
</ul>
Why This is the Place to Be
<ul>
<li>You will have a front-row seat to the Agentic revolution. If you want to solve the hardest problems in data discovery and see your work power the decision-making of thousands of people, let’s talk.</li>
</ul>
 
What We’re Looking For
<ul>
<li>The IR Specialist: You know your way around Lucene/Elasticsearch, embeddings, and ranking algorithms.</li>
<li>The Quality and Metrics Obsessive: You understand that "relevance" is subjective and love building evaluation frameworks (human-in-the-loop and LLM-based) to measure it. You are obsessed with relevance metrics (nDCG, MRR, Precision@K).</li>
<li>The Bridge Builder: You’re excited to apply traditional Information Retrieval (IR) wisdom to the cutting-edge world of Retrieval-Augmented Generation (RAG).</li>
</ul><div>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 <a href="https://twitter.com/databricks" target="_blank" rel="noopener noreferrer ugc">Twitter</a>, <a href="https://www.linkedin.com/company/databricks" target="_blank" rel="noopener noreferrer ugc">LinkedIn</a> and <a href="https://www.facebook.com/databricksinc" target="_blank" rel="noopener noreferrer ugc">Facebook</a>. 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 <a href="https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing" rel="noopener noreferrer ugc" target="_blank">here</a>. 
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.</div>

Databricks

Open jobs at Databricks

Applied AI Engineer, Learning Intelligence

Staff Software Engineer - AI/ML

Staff Fullstack Engineer, Agentic Applications

Staff Software Engineer (Search Ranking)

Staff Software Engineer- Search Quality

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