
Pinterest · San Francisco
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will...
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for
memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love,
and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s
unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re
looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll
explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know,
but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
As a machine learning intern in our Advance Technology Group at Pinterest, you will be exposed to a full spectrum of ML product
development. The team focuses on developing cutting-edge technologies for Pinterest’s visual understanding modules and recommender
systems. You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and
mentoring, while also having opportunities to deploy features to hundreds of millions of users or conduct research applicable for
paper submissions. We offer a 12-week fall internship program remotely or in our San Francisco, Palo Alto, Seattle, or New York
offices.
By applying to this role, you will be considered for multiple intern roles open across our various ML teams. Please only apply
once within the USA or Canada as multiple applications may delay our recruitment process.
Internships are 12 weeks paid from September 21 - December 11, 2026. Depending on the team, our fall internships will be located
either remote or hybrid in San Francisco, Palo Alto, New York or Seattle offices.
computer vision, representation learning, generative AI, and responsible AI.
training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems.
maintainable, secure, and aligned with team standards.
manager, and peers
Vision, Visual Search, User Understanding, Recommendation Systems, Reinforcement Learning, ML efficiency optimization,
Generative AI, and LLMs.
performance, security, and maintainability.
constraints.
Why Intern at Pinterest?
connections.
to gather for key moments of collaboration and connection
commutable distance from one of our Pinterest offices.
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide
greater transparency, we are sharing the base salary range for this position. Final salary is based on a number of factors
including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
US based applicants only
The salary for this position is $12,100 monthly.
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best
qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color,
ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions),
sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or
mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other
consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of
criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job
application process, please complete this form for support.
By submitting this application, I certify that all information submitted in my application and throughout the hiring process is
true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation
may disqualify me from employment consideration or result in termination if discovered after hire.
P-97 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse (CIDR 2021 paper), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Spark™ to support diverse workloads ranging from ETL to data science. As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art: * Query compilation and optimization * Distributed query execution and scheduling * Vectorized execution engine * Data security * Resource management * Transaction coordination * Efficient storage structures (encodings, indexes) * Automatic physical data optimization What we look for: * A passion for database systems, storage systems, distributed systems, language design, or performance optimization * Experience working towards a multi-year vision with incremental deliverables * Motivated by delivering customer value and impact * 5+ years of experience working in a related system (preferred) * Optional: PhD in databases or distributed systems 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 $166,000—$225,000 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.
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.
ABOUT DATABRICKS Databricks is the Data + AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 60% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe. ABOUT THE TEAM The Databricks AI Research organization is pushing the frontier of next-generation enterprise AI. We believe a company's data is its greatest competitive advantage, and we're building the models and agents that unlock it. Our work spans the full stack, from model training to advanced multi-agent systems. The Data Agent team within AI Research is dedicated to pioneering frontier enterprise data agents. Our research focuses on developing agents capable of autonomous planning, code generation, and multi-step workflow execution within intricate enterprise settings. The team's primary technical pillars include post-training enhancements, harness design, agentic reinforcement learning (RL), and the construction of specialized RL environments. As a member of this team, you will bridge the gap between cutting-edge AI research and product development by shipping direct improvements to Genie, Databricks' agent product that provides significant value to our user base. THE IMPACT YOU WILL HAVE * Develop the best post-training recipes to train enterprise Data agents, that are capable of autonomous planning, code generation, and multi-step workflow execution within intricate enterprise settings. * Partner closely with product teams to turn prototypes and research ideas into the best agentic experience for Databricks users. * Build systems that help the agent discover and use relevant lakehouse context, including tables, notebooks, code, and cell outputs, to produce more accurate and useful results. * Raise the technical bar for the team through strong design, execution, debugging, and mentorship, helping shape the long-term direction of agentic experiences at Databricks. WHAT WE LOOK FOR * BS, MS, or PhD in Computer Science or a related field. * 2+ years of experience in an applied research environment, with a track record of shipping research prototypes to production. * Experience in LLMs, agents, reinforcement learning, post-training workflows. * Ability to work effectively in a fast-moving environment that blends research exploration with product and engineering rigor. * Clear communication and strong cross-functional collaboration with researchers, engineers, and product stakeholders. 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 $190,000—$270,000 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.