Databricks

<p><strong>SLSQ327R638</strong></p>
<p> </p>
<p>The GTM Solutions &amp; Governance team sits within GTM StratOps/Analytics (SGO) and is tasked with making our GTM data estate trustworthy, enriched, and self-serviceable. As a distinct function from traditional analytics, we own the advanced AI/agent solutions and complex automation built on top of our data. You will work alongside experts in GTM Automation, GTM Alerting, Peer Similarity, and Data Governance to elevate how our GTM organization operates.</p>
<p><strong>The Role</strong></p>
<p>We are looking for a Senior GTM Analytics Engineer to build advanced generative AI applications, automated pipelines, and agentic solutions to optimize our revenue operations. You will own the development of data pipelines handling both structured and unstructured data, architect high-level AI implementations like Agentic CDPs, and drive our internal Databricks on Databricks (DBX@DBX) initiatives.</p>
<p><strong>Core Responsibilities</strong></p>
<ul>
<li>Agentic CDP &amp; Identity Resolution: Architect and deploy Agentic Customer Data Platform (CDP) capabilities to perform intelligent identity resolution, driving automated and highly accurate data enrichment for accounts and contacts.</li>
<li>GenAI &amp; Agent Architecture: Design LLM-powered systems and internal agents to automate KPI root-cause analysis, generate business insights, and streamline GTM communication.</li>
<li>Advanced Data Pipelines: Build and manage complex data pipelines to process structured and unstructured data, ensuring high-fidelity inputs for the GTM data estate while seamlessly integrating with our existing governance frameworks.</li>
<li>GTM Systems Integration: Understand the technology stack and how data flows between critical systems like Salesforce, Xactly, and 6sense to ensure unified data architecture.</li>
<li>Cross-Functional Partnership: Partner directly with Sales, Marketing, and RevOps leaders to turn strategic business problems into scalable, data-driven AI solutions.</li>
</ul>
<p> </p>
<p><strong>What We Look For</strong></p>
<ul>
<li>Technical Stack: You have expert proficiency in Python, SQL, and modern data pipelines. You also have experience with Salesforce or equivalent CRM systems.</li>
<li>Platform Expertise: You will work every day with a variety of data using Databricks’ lakehouse platform. You will become an expert in using Databricks and complementary AI technologies to build production-grade solutions.</li>
<li>Domain Experience: You typically have strong experience in data engineering, data science, or advanced analytics, with a background working closely with B2B sales, marketing, or finance data.</li>
<li>Advanced Analytics Background: You have a strong track record in B2B SaaS, machine learning, and generative AI deployment.</li>
<li>Execution Mindset: You excel in a collaborative environment and translate team member needs into clear deliverables. You work through dependencies, bottlenecks, and tradeoffs with ease.</li>
</ul><div><p><strong>About Databricks</strong></p>
<p><span>Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&amp;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 <a href="https://www.linkedin.com/company/databricks" rel="noopener noreferrer ugc" target="_blank">LinkedIn</a>, <a href="https://x.com/databricks" rel="noopener noreferrer ugc" target="_blank">X</a>, <a href="https://www.youtube.com/@Databricks" rel="noopener noreferrer ugc" target="_blank">YouTube</a>, and <a href="https://www.instagram.com/databricksinc/?hl=en" rel="noopener noreferrer ugc" target="_blank">Instagram</a>.<br /><br /><strong>Benefits<br /><br /></strong></span>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>.<br /><br /></p>
<p><strong>Our Commitment to Diversity and Inclusion</strong></p>
<p>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.</p>
<p><strong>Compliance</strong></p>
<p><strong><span>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.</span></strong></p></div>

Senior Go-To-Market (GTM) Analytics Engineer (AI & Pipelines)

<p>P-1930</p>
<p>At Databricks, we are passionate about enabling data and AI 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 and AI infrastructure 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 solve 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.</p>
<p>As part of the AI team, you'll build the platforms and products that power everything from data apps, AI agents, model training, model serving, and Vector Search. You'll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses, helping thousands of our customers democratize AI within their organizations. We're building the products and infrastructure that power the next generation of AI.</p>
<p>The Foundation Model Inference team is the backbone of Databricks’ generative AI capabilities. We build the infrastructure that enables our customers to serve, scale, and optimize frontier models with enterprise-grade reliability and performance. Our Foundation Model APIs provide a unified platform that gives customers access to LLMs with the governance, flexibility, and scalability required for enterprise production workloads.</p>
<p>We are looking for high-agency engineers who are excited to work on powering model inference at enterprise scale.</p>
<h3><strong>The impact you will have:</strong></h3>
<ul>
<li>Build LLM infrastructure powering large-scale inference workloads for customers through partner models (OpenAI, Anthropic, Gemini) and self-hosted models (Qwen, GPT-OSS, Llama)</li>
<li>Improve reliability, latency, and efficiency of distributed AI workloads</li>
<li>Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences</li>
<li>Shape how developers and data scientists build and interact with AI on Databricks</li>
</ul>
<h3><strong>What we look for:</strong></h3>
<ul>
<li>8+ years of experience in backend or infrastructure engineering</li>
<li>Experience with distributed systems, scalable APIs, or cloud-native infrastructure</li>
<li>Experience with real-time serving, ML infrastructure, or GPU orchestration</li>
<li>Familiarity with service-oriented architecture, deployment pipelines, and system observability</li>
</ul>
<h3><strong>Bonus points for:</strong></h3>
<ul>
<li>Exposure to platforms like SageMaker, Vertex AI, or Azure ML</li>
<li>Contributions to OSS projects like MLflow, PyTorch, Ray, vLLM, SGLang</li>
<li>Built developer platforms or internal tools supporting AI workflows</li>
</ul><div><div><div><p> </p>
<p><strong>Pay Range Transparency</strong></p>
<p><span>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>.<br /></span></p>
<p> </p></div><div>Local Pay Range</div><div><span>$190,000</span><span>—</span><span>$265,000 USD</span></div></div></div><div><p><strong>About Databricks</strong></p>
<p><span>Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&amp;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 <a href="https://www.linkedin.com/company/databricks" rel="noopener noreferrer ugc" target="_blank">LinkedIn</a>, <a href="https://x.com/databricks" rel="noopener noreferrer ugc" target="_blank">X</a>, <a href="https://www.youtube.com/@Databricks" rel="noopener noreferrer ugc" target="_blank">YouTube</a>, and <a href="https://www.instagram.com/databricksinc/?hl=en" rel="noopener noreferrer ugc" target="_blank">Instagram</a>.<br /><br /><strong>Benefits<br /><br /></strong></span>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>.<br /><br /></p>
<p><strong>Our Commitment to Diversity and Inclusion</strong></p>
<p>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.</p>
<p><strong>Compliance</strong></p>
<p><strong><span>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.</span></strong></p></div>

Staff Software Engineer- Foundation Model Inference

<p><strong>P-1930</strong></p>
<p>At Databricks, we are passionate about enabling data and AI 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 and AI infrastructure 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 solve 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.</p>
<p>As part of the AI team, you'll build the platforms and products that power everything from data apps, AI agents, model training, model serving, and Vector Search. You'll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses, helping thousands of our customers democratize AI within their organizations. We're building the products and infrastructure that power the next generation of AI.</p>
<p>We're hiring across multiple teams in our AI Engineering org, including the <strong>FMAPI (Foundation Model APIs)</strong> team — the unified serving layer for large language models across real-time and batch inference, powering model inference at enterprise scale. We are looking to hire high-agency engineers who bridge the gap between technical execution and product strategy.</p>
<h3><strong>The impact you will have:</strong></h3>
<ul>
<li>Build LLM infrastructure powering large-scale inference workloads for customers through partner models (OpenAI, Anthropic, Gemini) and self-hosted models (Qwen, GPT-OSS, Llama)</li>
<li>Shape the direction of the FMAPI product — from roadmap to execution — by leveraging deep customer empathy and direct engagement with enterprise users and model providers</li>
<li>Improve reliability, latency, and efficiency of distributed AI workloads</li>
<li>Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences</li>
<li>Shape how developers and data scientists build and interact with AI on Databricks</li>
</ul>
<h3><strong>What we look for:</strong></h3>
<ul>
<li>8+ years of experience in backend or infrastructure engineering</li>
<li>Experience with distributed systems, scalable APIs, or cloud-native infrastructure</li>
<li>Strong product and ownership mindset, with a focus on shipping user-facing value</li>
<li>Experience with real-time serving, ML infrastructure, or GPU orchestration</li>
<li>Familiarity with service-oriented architecture, deployment pipelines, and system observability</li>
<li>Strong programming skills in Scala, Go, or Python</li>
</ul>
<h3><strong>Bonus points for:</strong></h3>
<ul>
<li>Exposure to platforms like SageMaker, Vertex AI, or Azure ML</li>
<li>Built products that support AI workflows</li>
</ul><div><div><div><p> </p>
<p><strong>Pay Range Transparency</strong></p>
<p><span>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>.<br /></span></p>
<p> </p></div><div>Local Pay Range</div><div><span>$190,000</span><span>—</span><span>$265,000 USD</span></div></div></div><div><p><strong>About Databricks</strong></p>
<p><span>Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&amp;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 <a href="https://www.linkedin.com/company/databricks" rel="noopener noreferrer ugc" target="_blank">LinkedIn</a>, <a href="https://x.com/databricks" rel="noopener noreferrer ugc" target="_blank">X</a>, <a href="https://www.youtube.com/@Databricks" rel="noopener noreferrer ugc" target="_blank">YouTube</a>, and <a href="https://www.instagram.com/databricksinc/?hl=en" rel="noopener noreferrer ugc" target="_blank">Instagram</a>.<br /><br /><strong>Benefits<br /><br /></strong></span>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>.<br /><br /></p>
<p><strong>Our Commitment to Diversity and Inclusion</strong></p>
<p>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.</p>
<p><strong>Compliance</strong></p>
<p><strong><span>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.</span></strong></p></div>

Staff Software Engineer, Foundation Model API

<p>CSQ227R13</p>
<h2><strong>About Databricks</strong></h2>
<p>Databricks is The data and AI company. More than 10,000 organizations worldwide rely on the Databricks Data Intelligence Platform to unify data, analytics, and AI. Founded by the original creators of Lakehouse, Apache Spark™, Delta Lake, and MLflow, Databricks is building the foundation for organizations to put data and AI to work.</p>
<h3><strong>The impact you’ll have</strong></h3>
<p>As a Senior member of the Learning Platforms team, you will shape the technical direction of the systems that help employees, partners, and customers build the skills they need to succeed with data and AI. You will operate as a broad platform owner - moving fluidly from product strategy and architecture to the hands-on engineering, cross-functional alignment, and reliable operations.</p>
<p>You will lead the design and delivery of intelligent, data-driven learning experiences that connect content, skills, assessments, and business outcomes. This is a high-impact individual contributor role for an individual who can turn ambiguous business problems into secure, scalable products! </p>
<h3><strong>What you’ll do</strong></h3>
<ul>
<li>Own the architecture and technical strategy for a portfolio of learning platforms and enablement products, from early discovery through production operation and evolution.</li>
<li>Lead the design and implementation of AI-powered capabilities, including recommendation systems, skill inference, intelligent search, personalization, and analytics-driven learning workflows.</li>
<li>Build secure, privacy-aware data systems that integrate information across learning, workforce, customer, and operational platforms.</li>
<li>Develop Databricks-native applications, data pipelines, APIs, automations, and user experiences that make complex learning processes simple and scalable.</li>
<li>Establish strong engineering practices for reliability, observability, testing, release management, access control, and lifecycle ownership.</li>
<li>Make pragmatic decisions and define integration strategies across learning management systems, lab environments, content platforms, identity systems, and internal data products.</li>
<li>Partner with business leaders to define product direction, prioritize roadmaps, clarify trade-offs, and deliver measurable outcomes.</li>
<li>Navigate complex requirements involving security, privacy, compliance, governance, and responsible use of AI.</li>
<li>Lead cross-functional technical programs involving multiple engineering teams and senior stakeholders, creating clarity and momentum in ambiguous environments.</li>
<li>Mentor engineers, raise the technical bar, contribute to hiring, and create reusable patterns that help the broader organization move faster.</li>
<li>Serve as a technical thought leader internally and externally through architecture documents, technical presentations, reusable guidance, and community engagement.</li>
</ul>
<h3><strong>What we’re looking for</strong></h3>
<ul>
<li>5-7 years of experience designing, building, and operating production software or data platforms, with a track record of leading work across organizational boundaries.</li>
<li>Demonstrated experience owning architecture and technical direction for complex, multi-system products.</li>
<li>Strong full-stack or platform engineering background, with depth in backend services, APIs, data pipelines, cloud infrastructure, and modern web applications.</li>
<li>Experience designing and operating AI- or data-intensive systems, such as recommendation engines, inference pipelines, search, personalization, or analytics products.</li>
<li>Fluency in Python or a similar production programming language, plus strong SQL and experience with relational and analytical data systems.</li>
<li>Experience with cloud platforms, distributed systems, identity and access management, security controls, and production operations.</li>
<li>Strong judgment around data privacy, governance, least-privilege access, and responsible AI.</li>
<li>Ability to communicate clearly with engineers, product managers, security and legal partners, and senior business leaders.</li>
<li>A track record of delivering results with minimal oversight while bringing structure to ambiguous problems.</li>
<li>A collaborative leadership style that combines technical depth, product thinking, pragmatism, and a bias for action.</li>
</ul>
<h3><strong>Preferred qualifications</strong></h3>
<ul>
<li>Experience with Databricks products and technologies such as Databricks Apps, Lakehouse data architectures, Unity Catalog, Delta Lake, Lakebase, Workflows, SQL Warehouses, or the Databricks SDK.</li>
<li>Experience integrating learning, content, assessment, identity, HR, or customer-facing platforms.</li>
<li>Experience building systems that serve both internal users and external customers or partners.</li>
<li>Experience scaling automation and operational workflows across large user populations or high-volume data sources.</li>
<li>Experience with modern frontend frameworks such as React and application frameworks such as Flask or FastAPI.</li>
<li>Experience mentoring senior engineers or leading technical programs across several teams.</li>
<li>Evidence of technical thought leadership through conference talks, publications, open-source work, or industry communities.</li>
</ul>
<h3><strong>About the team</strong></h3>
<p>The Learning Platforms team builds the digital ecosystem behind Databricks learning and enablement. We combine software engineering, data, AI, and product thinking to improve how people discover content, develop skills, practice with the platform, and measure progress. Our work spans learner experience, intelligent recommendations, platform integrations, operational automation, cost efficiency, and reliable delivery at scale.</p><div><div><div><p> </p>
<p><strong>Pay Range Transparency</strong></p>
<p><span>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>.<br /></span></p>
<p> </p></div><div>Zone 1 Pay Range</div><div><span>$139,000</span><span>—</span><span>$191,050 USD</span></div></div><div><div>Zone 2 Pay Range</div><div><span>$125,000</span><span>—</span><span>$171,950 USD</span></div></div><div><div>Zone 3 Pay Range</div><div><span>$118,100</span><span>—</span><span>$162,350 USD</span></div></div><div><div>Zone 4 Pay Range</div><div><span>$111,200</span><span>—</span><span>$152,900 USD</span></div></div></div><div><p><strong>About Databricks</strong></p>
<p><span>Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&amp;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 <a href="https://www.linkedin.com/company/databricks" rel="noopener noreferrer ugc" target="_blank">LinkedIn</a>, <a href="https://x.com/databricks" rel="noopener noreferrer ugc" target="_blank">X</a>, <a href="https://www.youtube.com/@Databricks" rel="noopener noreferrer ugc" target="_blank">YouTube</a>, and <a href="https://www.instagram.com/databricksinc/?hl=en" rel="noopener noreferrer ugc" target="_blank">Instagram</a>.<br /><br /><strong>Benefits<br /><br /></strong></span>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>.<br /><br /></p>
<p><strong>Our Commitment to Diversity and Inclusion</strong></p>
<p>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.</p>
<p><strong>Compliance</strong></p>
<p><strong><span>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.</span></strong></p></div>

Applied AI Engineer, Learning Intelligence

<p><em>RDQ427R109</em></p>
<p> </p>
<p>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.</p>
<p> </p>
<p>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.</p>
<p> </p>
<p><strong>The impact you'll have:</strong></p>
<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>
<p> </p>
<p><strong>What we look for:</strong></p>
<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>
<p> </p>
<p><strong>Nice to have:</strong></p>
<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>
<p> </p><div><div><div><p> </p>
<p><strong>Pay Range Transparency</strong></p>
<p><span>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>.<br /></span></p>
<p> </p></div><div>Local Pay Range</div><div><span>$192,000</span><span>—</span><span>$260,000 USD</span></div></div></div><div><p><strong>About Databricks</strong></p>
<p><span>Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&amp;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 <a href="https://www.linkedin.com/company/databricks" rel="noopener noreferrer ugc" target="_blank">LinkedIn</a>, <a href="https://x.com/databricks" rel="noopener noreferrer ugc" target="_blank">X</a>, <a href="https://www.youtube.com/@Databricks" rel="noopener noreferrer ugc" target="_blank">YouTube</a>, and <a href="https://www.instagram.com/databricksinc/?hl=en" rel="noopener noreferrer ugc" target="_blank">Instagram</a>.<br /><br /><strong>Benefits<br /><br /></strong></span>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>.<br /><br /></p>
<p><strong>Our Commitment to Diversity and Inclusion</strong></p>
<p>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.</p>
<p><strong>Compliance</strong></p>
<p><strong><span>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.</span></strong></p></div>

Databricks

Open jobs at Databricks

Senior Go-To-Market (GTM) Analytics Engineer (AI & Pipelines)

Staff Software Engineer- Foundation Model Inference

Staff Software Engineer, Foundation Model API

Applied AI Engineer, Learning Intelligence

Staff Software Engineer - AI/ML

Working for Databricks?

Featured companies