Software Engineer, Graphics & Media

P-1284 ABOUT THIS ROLE As a software engineer for GenAI inference, you will help design, develop, and optimize the inference engine that powers Databricks’ Foundation Model API. You’ll work at the intersection of research and production, ensuring our large language model (LLM) serving systems are fast, scalable, and efficient. Your work will touch the full GenAI inference stack — from kernels and runtimes to orchestration and memory management. WHAT YOU WILL DO * Contribute to the design and implementation of the inference engine, and collaborate on model-serving stack optimized for large-scale LLMs inference * Collaborate with researchers to bring new model architectures or features (sparsity, activation compression, mixture-of-experts) into the engine * Optimize for latency, throughput, memory efficiency, and hardware utilization across GPUs, and accelerators * Build and maintain instrumentation, profiling, and tracing tooling to uncover bottlenecks and guide optimizations * Develop and enhance scalable routing, batching, scheduling, memory management, and dynamic loading mechanisms for inference workloads * Support reliability, reproducibility, and fault tolerance in the inference pipelines, including A/B launches, rollback, and model versioning * Integrate with federated, distributed inference infrastructure – orchestrate across nodes, balance load, handle communication overhead * Collaborate cross-functionally: with platform engineers, cloud infrastructure, and security/compliance teams * Document and share learnings, contributing to internal best practices and open-source efforts when possible WHAT WE LOOK FOR * BS/MS/PhD in Computer Science, or a related field * Strong software engineering background (3+ years or equivalent) in performance-critical systems * Solid understanding of ML inference internals: attention, MLPs, recurrent modules, quantization, sparse operations, etc. * Hands-on experience with CUDA, GPU programming, and key libraries (cuBLAS, cuDNN, NCCL, etc.) * Comfortable designing and operating distributed systems, including RPC frameworks, queuing, RPC batching, sharding, memory partitioning * Demonstrated ability to uncover and solve performance bottlenecks across layers (kernel, memory, networking, scheduler) * Experience building instrumentation, tracing, and profiling tools for ML models * Ability to work closely with ML researchers, translate novel model ideas into production systems * Ownership mindset and eagerness to dive deep into complex system challenges * Bonus: published research or open-source contributions in ML systems, inference optimization, or model serving     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 here.   Local Pay Range $142,200—$204,600 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 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. For specific details on the benefits offered in your region click here. 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.

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. At Airtable, we're passionate about democratizing software creation — empowering anyone to build powerful, flexible tools without writing code. With our shift to an AI-native platform, customers can now generate full apps and deploy AI agents directly into their workflows. Data engineering plays a critical role in this evolution by delivering the insights our teams rely on to improve user experience, measure agent impact, and understand how the business is performing at scale. As a Software Engineer, Data at Airtable, you'll make an enormous contribution to our data engineering efforts. You'll design and own mission-critical data pipelines to enable decision-making, partner with company leaders to create scalable data solutions, and launch innovative alerting and visualization solutions. THE TEAM Our team is embedded in how Airtable understands itself as a business, working closely with Data Science and Analytics. What's unusual here: the platform you're instrumenting is the same one your customers use every day. When Airtable ships a new AI agent capability, you're among the first to wire it up, measure its adoption, and influence what gets built next. Product & AI Data Infrastructure This team builds and owns the foundational data pipelines that power product analytics across Airtable. As Airtable shifts to an AI-native platform, our work increasingly involves instrumenting and measuring AI product usage, building event pipelines for AI agents, surfacing AI-native adoption metrics in core business tables, and developing AI-powered data discovery tooling, including vector search over our catalog metadata. We partner closely with product analytics, product engineering, and data infrastructure to turn business questions into well-modeled, trustworthy data. WHAT YOU'LL DO * Work across our engineering organization and stakeholders from data science, growth, sales, marketing, and product to understand the data needs of the business and produce pipelines, data marts, and other solutions that enable better decision-making. * Design and maintain our foundational business tables in order to simplify analysis and reporting across the entire company, including AI usage metrics surfaced to executive stakeholders. * Use AI tools as a daily part of how you work, from LLM-assisted pipeline development and debugging to exploring our catalog through AI-powered discovery, and bring a curiosity for where this tooling is heading next. * Build and enforce a pattern language across our data stack, ensuring pipelines and tables are consistent, accurate, and well-understood. * Continue to improve the performance and reliability of our data warehouse. * Partner with data scientists, analytics engineers, and business stakeholders to translate ambiguous business questions into well-scoped data solutions. WHO YOU ARE * You have 3-8+ years of professional experience designing, creating, and maintaining scalable data pipelines, preferably in Airflow. * You've wrangled enough data to understand how often the complex systems that produce it can go wrong, and you build with that in mind. * You are proficient in at least one programming language (preferably Python) and are willing to pick up others as the work demands. * You are highly effective with SQL and understand how to write and tune complex queries. * You're genuinely curious about how AI is reshaping data engineering and you're actively experimenting, not just watching from the sidelines. Whether that's using LLMs to write and debug pipelines faster, thinking through how to model agent behavior as data, or exploring what smarter data discovery could look like, you bring enthusiasm for figuring it out. * You're passionate and thoughtful about building systems that enhance human understanding. * You communicate with clarity and precision in written form and have experience conveying findings through graphs and visualizations.   ---------------------------------------------------------------------------------------------------------------------------------- Compensation awarded to successful candidates will vary based on their work location, relevant skills, and experience. Our total compensation package also includes the opportunity to receive benefits, restricted stock units, and may include incentive compensation. To learn more about our comprehensive benefit offerings, please check out Life at Airtable. For work locations in the San Francisco Bay Area, Seattle, New York City, and Los Angeles, the base salary range for this role is: $179,500—$221,500 USD For all other work locations (including remote), the base salary range for this role is: $162,000—$199,800 USD Please see our Privacy Notice for details regarding Airtable’s collection and use of personal data relating to the application and recruitment process by clicking here. For applicants that live in or have a link to Australia, please see this Privacy Collection Statement for details regarding Airtable's collection and use of personal data relating to the application and recruitment process. 🔒 Stay Safe from Job Scams All official Airtable communication will come from an @airtable.com email address. We will never ask you to share sensitive information or purchase equipment during the hiring process. If in doubt, contact us at hr@airtable.com. Learn more about avoiding job scams here.