Senior Machine Learning Engineer - Recommendation and Personalization

About Faire Faire is an online wholesale marketplace focused on supporting independent retailers. By connecting small businesses with products from around the world, Faire aims to help local shops compete with major players like Walmart and Amazon. The company uses technology, data analytics, and machine learning to provide insights and tools that level the playing field for entrepreneurs everywhere. Faire’s work strengthens local economies by enabling independent businesses to thrive. The team values resourcefulness, intelligence, and a commitment to community. Those who believe in supporting local businesses will find a shared purpose here. Role Overview: Data Science Intern – Personalization & Recommender Systems This internship focuses on building and improving machine learning systems that power search, personalization, and recommendations for Faire’s marketplace. Interns will join a team dedicated to developing algorithms that help local retailers discover relevant products and compete with larger competitors. The team welcomes Master’s and PhD students with a background in recommender systems, personalization, or applied machine learning. Who We’re Looking For Strong interest in recommender systems and personalization Experience applying modern machine learning techniques to ranking or representation learning PhD candidates: a record of publications or submissions to top conferences (such as KDD, RecSys, ICML, NeurIPS, WWW, SIGIR) Master’s candidates: meaningful research projects, internships, or open-source contributions in related areas What You’ll Work On Design and build advanced recommender systems for product ranking and discovery Develop methods for user and item representation learning Collaborate with machine learning engineers to move research solutions into production Tackle personalization challenges that impact millions of recommendations each day Location San Francisco, CA

Crunchyroll serves a global community of anime fans, connecting over 100 million people across more than 200 countries and territories. The platform offers streaming, theatrical releases, games, merchandise, and events, all centered around anime stories and characters. Role overview The Senior Applied Scientist in Recommendation and Personalization leads scientific development for Crunchyroll’s recommendation, ranking, and decisioning systems. The focus is to help fans discover and engage with anime series, movies, manga, merchandise, and games. This position collaborates with Machine Learning Engineers, Product Managers, Engineering, Marketing, and Content teams to enhance Crunchyroll’s personalized experiences. What you will do Lead research and applied science projects in personalization, covering problem definition, data exploration, model development, evaluation, experimentation, and iteration. Define what outstanding personalization looks like for Crunchyroll across app and web interfaces, email campaigns, and integrated systems for video, ecommerce, and manga. Demonstrate the impact of personalization efforts using evidence and metrics. Partner with engineering teams to bring scientific solutions into production. Reporting structure This role reports to the Director of Data Science and Machine Learning within the Center for Data and Insights. Location and schedule This position is based in Los Angeles, California, or San Francisco, CA. Crunchyroll follows a hybrid schedule, with in-office attendance required three days per week: Tuesday, Wednesday, and Thursday.

About KreaKrea is at the forefront of developing advanced AI creative tools designed to enhance and empower human creativity. Our mission is to create intuitive and controllable AI solutions that allow creatives to express themselves across various formats including text, images, video, sound, and 3D.About the PositionWe are seeking a talented Machine Learning Engineer to lead the design and implementation of Krea’s personalization and recommendation systems from the ground up. You will take full ownership of how we comprehend user preferences, curate engaging content, and customize generative models to reflect individual aesthetics.This role sits at the exciting intersection of recommendation systems, representation learning, and generative imaging and video technologies.Your ResponsibilitiesLead the architecture and development of Krea’s personalization and recommendation framework, overseeing the technical direction from inception to deployment.Craft algorithms that effectively model user preferences and tastes, enabling our systems to adapt to individual styles and aesthetics.Develop high-quality, curated feeds that strike a balance between exploration, personalization, and aesthetic coherence.Collaborate closely with our model and research teams to co-create personalization mechanisms that shape how our generative models learn, adapt, and express creative styles.Contribute to research in personalized image generation, with a focus on style, taste, and subjective quality.Work in tandem with product, design, and research teams to define what “good personalization” means in a creative context.Take systems from initial research and prototyping stages through to production, ongoing iteration, and enhancement.

At Philo, we are a dedicated team of technology and product enthusiasts committed to reshaping the television landscape. We blend cutting-edge technology with the captivating medium of television to create the ultimate viewing experience. Our mission is to enhance streaming capabilities through innovative cloud delivery and sophisticated machine learning algorithms that personalize content discovery. As a Senior Machine Learning Engineer specializing in Recommendation Systems, you will be at the forefront of our content personalization initiatives, significantly enhancing user engagement and satisfaction. Your expertise will help ensure that every time users open the Philo app, they find something they want to watch. In this pivotal role, you will spearhead the development of advanced algorithms and large-scale systems that drive Philo's recommendation engine. Collaborating closely with data science, product, infrastructure, and backend engineering teams, you will tackle complex machine learning challenges and develop innovative, data-driven solutions that enhance content discovery and foster user retention.

Pinterest is looking for a PhD Fall Machine Learning Intern with a focus on visual, multimodal, and recommender systems. This internship centers on supporting advanced machine learning projects alongside skilled engineers and researchers. Role overview The position involves contributing to ongoing research and development in machine learning. Interns will have the chance to work on projects that explore visual understanding and recommendation technologies, learning from experienced team members throughout the process. Collaboration Expect to work closely with engineers and researchers who specialize in machine learning. The environment encourages sharing ideas and building solutions that impact Pinterest’s products. Locations San Francisco, CA, US Palo Alto, CA, US Seattle, WA, US New York, NY, US

About Quizlet:At Quizlet, our vision is to empower every learner to achieve their educational goals in the most effective and enjoyable manner. As a thriving $1B+ educational platform, we serve two-thirds of U.S. high school students and half of college students, facilitating over 1 billion learning interactions weekly.By integrating cognitive science with advanced machine learning techniques, we tailor and enhance the learning experience for students, professionals, and lifelong learners alike. Our enthusiasm lies in the potential to support more learners through diverse methodologies and tools.Let's Shape the Future of Learning TogetherJoin us in designing and implementing AI-driven learning solutions that scale globally, unlocking the potential of learners everywhere.About the Team:The Personalization & Recommendations team is dedicated to crafting customized learning experiences that enable millions of learners to study more effectively. We are seeking Machine Learning Engineers across Senior to Staff levels (including Sr. Staff) to join our innovative team.You will leverage your expertise in modern recommender systems—encompassing deep learning-based retrieval, embeddings, and multi-stage ranking—to enhance Quizlet's personalization capabilities. Collaborating at the nexus of machine learning, product development, and scalable systems, you will ensure our recommendations are efficient, ethical, and aligned with learner outcomes, privacy, and fairness.This is an onsite position, requiring team members to work in the office at least three days a week: Monday, Wednesday, and Thursday, as well as additional days as needed. We believe this in-office collaboration fosters efficiency, enhances teamwork, and promotes both personal and organizational growth.

About FaireFaire is a dynamic online wholesale marketplace committed to the belief that the future is local. Independent retailers around the globe are generating more revenue than major corporations like Walmart and Amazon combined, yet they often lack the visibility and resources to compete. At Faire, we harness the power of technology, data, and machine learning to connect this vibrant community of entrepreneurs worldwide. Imagine your favorite local boutique—our platform helps them uncover the finest products from around the globe to offer in their stores. With our innovative tools and insights, we strive to level the playing field, enabling small businesses everywhere to thrive against the giants of retail.By championing the growth of independent businesses, Faire not only supports local economies but also creates a positive economic impact on communities worldwide. We are seeking intelligent, resourceful, and passionate individuals to join us in our mission to empower the shop local movement. If you share our belief in community, we invite you to become part of ours.About this role:At Faire, we leverage cutting-edge machine learning and data insights to transform the wholesale industry, equipping local retailers to compete with e-commerce behemoths. Our team of skilled data scientists and machine learning engineers is dedicated to crafting algorithmic solutions for search, personalization, recommendation systems, and ranking. Our mission is to empower local retail businesses with the necessary tools for success.The Data Science team plays a crucial role in creating and maintaining a variety of algorithms and models that drive our marketplace. We are committed to developing machine learning models that support our customers' growth.We have several openings available in the Data organization.Search: Experience with GenAI and LLMs for search optimization, query understanding, retrieval, and ranking is preferred.Personalization: Experience in personalizing recommendation surfaces through embeddings, near-real-time streaming signals, explore-exploit, and diversification is a plus.Retailer Growth: Experience in developing machine learning solutions to enhance growth through paid marketing bidding, targeting efficiency, and sitemap optimization is preferred.Retailer Products: Experience with predictive modeling, Redshift, and Mode Analytics is advantageous.

Internship Dates: June 1, 2026 – August 21, 2026Location: United States Role overview Airbnb’s Core Data Science team is seeking a Data Science Intern (PhD) for Summer 2026. This team addresses complex business questions through data research, modeling, and empirical analysis, with a focus on scientific innovation and practical improvements to the Airbnb platform. The internship centers on the Trip Intelligence working group, which develops and enhances the GSAT model, an AI-driven system that measures guest satisfaction using diverse data sources. What you will do Review academic research to find ways to incorporate active learning into existing models Investigate new approaches for dataset labeling to support model training and evaluation Build and test an active learning pipeline for the GSAT model, then analyze its performance Experiment with techniques to improve label quality, including using LLM labeling agents Internship experience This internship offers practical experience with Generative AI and the opportunity to work on projects that directly affect Airbnb’s guest experience. Interns will engage in exploratory research and gain insight into industry data science practices.

Join Samba TV, a pioneering company that is redefining the global viewing experience through advanced data and technology. Our mission is to fundamentally enhance how audiences engage with streaming and broadcast video, empowering media companies to connect with viewers in innovative ways. Our unique perspective on culture is shaped by our expansive data footprint and AI-driven insights.We are looking for enthusiastic and detail-oriented interns to be part of our Measurement team. In this role, you will collaborate with Measurement Partners to explore how our solutions influence advertising decisions for our publishers and platform businesses.

Role Overview DoorDash is hiring a Data Science Manager to lead a team of data scientists working on projects that use data to improve DoorDash’s services. This role involves managing team members, setting direction for analytical model development, and shaping strategies that influence decisions across the company. What You Will Do Oversee and mentor a team of data scientists Guide the development of analytical models and data-driven strategies Work with teams from different departments to spot opportunities for improvement Deliver insights that help DoorDash connect people with top local options Locations San Francisco, CA Sunnyvale, CA Seattle, WA New York, NY Chicago, IL Austin, TX

Join our dynamic team at Liquid AI as a Member of Technical Staff where you will leverage your expertise in applied machine learning and recommendation systems to drive innovative solutions. You will collaborate with a talented group of professionals in a fast-paced environment, contributing to the development of advanced algorithms that enhance user experience and operational efficiency.

Join Pinterest as a Manager II in Data Science and play a vital role in shaping our data-driven strategies. Lead a talented team of data scientists to leverage analytics and machine learning, driving impactful insights that enhance user experience and business outcomes.In this position, you will collaborate cross-functionally with engineering, product management, and marketing teams, ensuring that analytics is deeply integrated into our decision-making processes.

Join us in making a difference! We’re hiring! At GoFundMe, we pride ourselves on being the world’s leading platform dedicated to empowering individuals and communities to support one another. By bringing together people and nonprofits, we facilitate a safe and easy way for individuals to seek and provide help, having collectively raised over $40 billion since our inception in 2010. We are in search of a talented Data Science Manager who will architect and spearhead the future of marketing data science at GoFundMe. This pivotal role involves developing and scaling applied data science and AI frameworks that enable our Marketing, Growth, and Finance teams to make informed, ROI-positive investment choices. You will function as both a leader and mentor within a skilled team of data scientists, driving innovation while ensuring high standards of delivery. Candidates for this role must be located in the San Francisco Bay Area, with an in-office presence required three times a week. Your Responsibilities: Establish a robust AI and data science infrastructure: Design scalable data pipelines, reusable modeling frameworks, and reliable experimentation platforms to support critical marketing and growth decisions. Lead comprehensive data science and AI initiatives: Oversee projects from initial requirements gathering through to feature engineering, modeling, validation, deployment, and ongoing monitoring. Set best practices: Advocate for standards in model governance, reproducibility, data quality, and system reliability, ensuring sustainable and trustworthy AI integration. Innovate in marketing science: Utilize advanced methodologies such as causal inference, uplift modeling, multi-touch attribution, and media mix modeling to derive insights and enhance spending effectiveness. Enhance forecasting and ROI modeling: Develop budget allocation frameworks and predictive models that inform long-term planning and marketing efficiency. Collaborate across departments: Partner with leaders from Marketing, Growth, Product, Engineering, and Finance to synchronize analytics initiatives with revenue objectives. Invest in talent development: Mentor and guide a high-performing team of data scientists, fostering a culture of technical excellence, curiosity, and practical innovation. Push the boundaries of applied AI in marketing: Assess emerging generative and predictive AI techniques for audience segmentation, creative optimization, personalization, and enhancing campaign efficiency.

Join Lyft as a Data Science Manager in our Mapping team, where you'll play a crucial role in shaping the future of transportation. You'll lead a talented team of data scientists, leveraging data to enhance our mapping platform and improve user experiences.In this dynamic environment, you will collaborate with cross-functional teams to derive insights from vast datasets, develop innovative solutions, and drive strategic initiatives. Your leadership will empower your team to explore new approaches in data science, making a significant impact on our products and services.

Join OpenAI's Integrity Data Science team, where our mission revolves around the responsible deployment of powerful AI technologies. We are dedicated to ensuring that our users can trust our products by developing measurement systems, experimental practices, and strategies to detect and mitigate misuse, fraud, and evolving adversarial behaviors.As we expand the scope and urgency of our Integrity initiatives across various product surfaces and market strategies, we are seeking a passionate Data Science Manager. In this role, you will play a pivotal role in scaling our team, enhancing execution across multiple Integrity domains, and fostering collaboration with Product, Engineering, Operations, and related teams (e.g., Growth, Ads).This position is located at our San Francisco headquarters (in-office).

Join our dynamic team at Sonsoft Inc. as a Data Science Analytics Associate! In this role, you will delve into data to extract insights that will drive our decision-making processes. You will work closely with cross-functional teams to analyze trends, develop models, and present findings that will contribute to our business strategies.

Role Overview Mercury is hiring a Senior Data Science Manager to guide key data initiatives as the company continues to grow. This role leads a skilled team of data scientists, applying advanced analytics to uncover insights that shape strategy and improve how the business operates. What You Will Do Lead and mentor a team of data scientists Use analytics to inform strategic decisions and drive operational improvements Work with teams across the company to find ways data can strengthen products and services Location This position is open to candidates based in San Francisco, CA; New York, NY; Portland, OR; or remote within Canada or the United States.

About Northbeam Northbeam builds marketing intelligence tools for eCommerce brands. The platform delivers a unified view of business data, with advanced attribution modeling and customizable dashboards. Clients use Northbeam to track advertising spend, understand the customer journey, and drive profitable growth. The company is growing quickly and scaling its product for broader adoption. Northbeam values motivated, collaborative professionals who care about personal growth and high standards. The team operates remotely across the US, with offices in San Francisco and Los Angeles. Data Science at Northbeam The Data Science team serves as the company’s intelligence backbone. The group owns marketing measurement and optimization, improving core methodologies like Media Mix Modeling (MMM), Incrementality testing, multi-touch attribution (MTA), calibration and validation frameworks, and large-scale experimentation systems. The team also delivers AI-powered insights and recommendations, building scientific systems that are reusable, scalable, and validated to enhance Northbeam’s products and customer value. Director of Data Science: Role Overview Northbeam is hiring a Director of Data Science to grow and lead a structured, multi-faceted data science organization. The team’s scope includes MMM, Incrementality, Insights, and Recommendation systems. This role reports to the VP of Data Science and will help scale the team from its current size to about 10 data scientists over the next year. The Director will shape both the technical roadmap and the organizational structure, setting priorities and guiding resource allocation for maximum impact. Responsibilities include managing multiple technical initiatives in parallel, maintaining scientific rigor, ensuring production quality, and supporting effective cross-functional work. The role requires comfort with startup ambiguity, strong technical depth, and a hands-on approach to execution. Candidates who thrive in early-stage settings and enjoy building new systems will find this work rewarding. Location This is a remote position open to candidates based in the USA.

Whatnot is a livestream shopping platform connecting buyers and sellers across North America and Europe. The marketplace covers a wide range of categories, from trading cards and electronics to fashion and live plants. Sellers use the platform to build businesses, while the team works to shape the future of live commerce in Western markets without relying on a set formula. The company operates as a remote-first organization, with co-located hubs in the US, UK, Ireland, Poland, Germany, and Australia. Agility and a focus on user needs drive the team’s approach, with projects chosen for their measurable impact. Whatnot has been recognized among the fastest growing marketplaces and was ranked #1 Best Startup Employer in America by Forbes. For more about the team and values, visit the careers page, the news blog, or the engineering blog.