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.

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.

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

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.

At Lyft, our mission is to connect and serve communities by fostering an inclusive work environment where every team member feels valued and empowered to excel.With over half a billion rides completed, Lyft is tackling complex challenges in a fast-evolving landscape filled with extensive data and innovative solutions across various domains including Marketplace, Mapping, Fraud Prevention, Trust & Safety, and Growth. As we redefine transportation with our next-generation platform, we utilize advanced machine learning techniques that process peta-byte scale data to create low-cost, ultra-immersive transportation solutions that enhance lives. Our dedicated Machine Learning Engineers are at the forefront of these efforts, crafting solutions that significantly influence our core business operations.If you are a critical thinker with a robust background in machine learning workflows, passionate about leveraging data to solve business challenges, and thrive in a dynamic, collaborative setting, we want to hear from you!As a Senior Machine Learning Engineer, you will design and implement algorithms that drive the core services and influential products of our platform. The range of challenges we tackle is remarkably diverse, spanning transportation, economics, forecasting, mapping, safety, personalization, and adaptive control. We are eager to welcome motivated experts in these fields who are excited about developing reliable ML systems and solving problems through data in an innovative and fast-paced environment.

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

Join Us in Building a Safer World.At TRM Labs, we specialize in blockchain analytics and AI solutions aimed at assisting law enforcement, national security agencies, financial institutions, and cryptocurrency businesses in identifying, investigating, and preventing crypto-related fraud and financial crime. Our innovative platforms leverage blockchain intelligence and AI technology to trace funds, detect illicit activity, and construct comprehensive threat profiles. Trusted by leading organizations worldwide, TRM Labs is committed to enabling a safer and more secure environment for all.Our AI Engineering Team is dedicated to pioneering next-generation AI applications, particularly in the realm of Large Language Models (LLMs) and agentic systems. Our goal is to develop resilient pipelines and high-performance infrastructure that facilitate the swift, safe, and scalable deployment of AI systems.We manage extensive petabyte-scale pipelines, ensuring model serving with millisecond latency while providing the necessary observability and governance to make AI production-ready. Our team actively evaluates and integrates leading-edge tools in the LLM and agent space, including open-source stacks, vector databases, evaluation frameworks, and orchestration tools to accelerate TRM’s innovation pace.As a Senior or Staff ML Systems Engineer – LLM, you will play a pivotal role in constructing and scaling our technical infrastructure for AI/ML systems. Your responsibilities will include:Creating reusable CI/CD workflows for model training, evaluation, and deployment, integrating tools such as Langfuse, GitHub Actions, and experiment tracking.Automating model versioning, approval processes, and compliance checks across various environments.Developing a modular and scalable AI infrastructure stack that encompasses vector databases, feature stores, model registries, and observability tools.Collaborating with engineering and data science teams to embed AI models and agents into real-time applications and workflows.Continuously assessing and incorporating state-of-the-art AI tools (e.g., LangChain, LlamaIndex, vLLM, MLflow, BentoML).Promoting AI reliability and governance while enabling experimentation, ensuring compliance, security, and continuous uptime.Enhancing AI/ML Model Performance and ensuring data accuracy and consistency, leading to improved model training and inference.Implementing infrastructure to facilitate both offline and online evaluation of LLMs and agents.

Join Scale AI's ML platform team (RLXF) as a Machine Learning Research Engineer, where you will play a pivotal role in developing our advanced distributed framework for training and inference of large language models. This platform is vital for enabling machine learning engineers, researchers, data scientists, and operators to conduct rapid and automated training, as well as evaluation of LLMs and data quality.At Scale, we occupy a unique position in the AI landscape, serving as an essential provider of training and evaluation data along with comprehensive solutions for the entire ML lifecycle. You will collaborate closely with Scale's ML teams and researchers to enhance the foundational platform that underpins our ML research and development initiatives. Your contributions will be crucial in optimizing the platform to support the next generation of LLM training, inference, and data curation.If you are passionate about driving the future of AI through groundbreaking innovations, we want to hear from you!

Join Anthropic as a Machine Learning Systems Engineer within our Encodings and Tokenization team, where you'll play a pivotal role in refining and optimizing our tokenization systems across Pretraining and Finetuning workflows. By bridging the gap between our Pretraining and Finetuning teams, you will help shape the essential infrastructure that enhances how our AI models learn from diverse data. Your contributions will be crucial in ensuring our AI systems remain reliable, interpretable, and steerable, driving forward our mission of developing beneficial AI technologies.

About UsAt Applied Compute, we specialize in creating Specific Intelligence solutions for enterprises, developing agents that learn continuously from an organization’s processes, data, expertise, and objectives. We recognize a significant gap between the capabilities of AI models in isolation and their practical applications in real-world business contexts. Our systems often fall short because they lack adaptability to feedback. To address this, we are building a continual learning infrastructure that captures context, memory, and decision-making processes throughout the enterprise, enabling specialized agents to effectively execute real tasks.What Excites Us: We operate at a unique intersection where our product team constructs the platform that fuels a new generation of digital coworkers. Our research team pushes the boundaries of post-training and reinforcement learning, creating innovative product experiences. Our applied research engineers collaborate closely with clients to deploy models into production. This blend of strong product focus, deep research, and hands-on customer engagement is crucial for integrating AI into the enterprise. We are product-driven, research-informed, and actively engaged with our clients.Our Team: Our diverse team consists of engineers, researchers, and operators, many of whom are former founders. We have built RL infrastructure at leading organizations like OpenAI and Scale AI, and developed systems at Together, Two Sigma, and Watershed. We proudly serve Fortune 50 clients alongside companies like DoorDash, Mercor, and Cognition. Our work is supported by renowned investors, including Benchmark, Sequoia, and Lux.Who Thrives in Our Environment: We seek individuals eager to apply cutting-edge research and complex systems to tackle real-world challenges. You should be adept at quickly adapting to new environments, whether it’s a fresh codebase, a client’s data architecture, or an unfamiliar problem domain. A genuine enjoyment of customer interactions—listening, empathizing, and understanding how tasks are accomplished within their organizations—is essential. Those with entrepreneurial backgrounds, extensive side projects, or demonstrated end-to-end ownership typically excel in our company.

OverviewPluralis Research is at the forefront of innovation in Protocol Learning, specializing in the collaborative training of foundational models. Our approach ensures that no single participant ever has or can obtain a complete version of the model. This initiative aims to create community-driven, collectively owned frontier models that operate on self-sustaining economic principles.We are seeking experienced Senior or Staff Machine Learning Engineers with over 5 years of expertise in distributed systems and large-scale machine learning training. In this role, you will design and implement a groundbreaking substrate for training distributed ML models that function effectively over consumer-grade internet connections.

About Our TeamJoin the innovative Sora team at OpenAI, where we are at the forefront of developing multimodal capabilities for our foundation models. Our hybrid research and product team is dedicated to seamlessly integrating multimodal functionalities into our AI solutions, ensuring they are dependable, user-centric, and aligned with our vision of benefiting society at large.Role OverviewAs a Machine Learning Engineer specializing in Distributed Data Systems, you will be instrumental in designing and scaling the infrastructure that facilitates large-scale multimodal training and evaluation at OpenAI. Your role will involve managing complex distributed data pipelines, collaborating closely with researchers to convert their requirements into robust, production-ready systems, and enhancing pipelines that are essential for Sora's rapid iteration cycles.We are seeking detail-oriented engineers with extensive experience in distributed systems who thrive in high-stakes environments and excel in building resilient infrastructure.This position is located in San Francisco, CA, and follows a hybrid work model, requiring three days in the office each week. We also provide relocation assistance for new team members.Key Responsibilities:Design, implement, and maintain data infrastructure systems, including distributed computing, data orchestration, distributed storage, streaming infrastructure, and machine learning systems, with a focus on scalability, reliability, and security.Ensure our data platform can scale exponentially while maintaining high reliability and efficiency.Collaborate with researchers to gain a deep understanding of their requirements, translating them into production-ready systems.Strengthen, optimize, and manage critical data infrastructure systems that support multimodal training and evaluation.You Will Excel in This Role If You:Possess strong experience with distributed systems and large-scale infrastructure, coupled with a keen interest in data.Exhibit meticulous attention to detail and a commitment to building and maintaining reliable systems.Demonstrate solid software engineering fundamentals and effective organizational skills.Thrive in environments characterized by ambiguity and rapid change.About OpenAIOpenAI is a trailblazing AI research and deployment organization committed to ensuring that general-purpose artificial intelligence serves humanity. We continuously push the boundaries of AI capabilities and strive to create technology that benefits everyone.

Join our innovative Match Team as a Senior Machine Learning Engineer at Enigmaio, where you will play a pivotal role in developing advanced algorithms and models that enhance our matching capabilities. You will collaborate with cross-functional teams to design, implement, and optimize machine learning solutions that drive business outcomes.

About Taskrabbit:Taskrabbit is an innovative marketplace platform that seamlessly connects individuals with Taskers to manage everyday home tasks, including furniture assembly, handyman services, moving assistance, and much more.At Taskrabbit, we aim to transform lives one task at a time. We celebrate innovation, inclusion, and hard work, fostering a collaborative, pragmatic, and fast-paced culture. We seek talented, entrepreneurially minded, data-driven individuals who possess a passion for empowering others to pursue their passions. In partnership with IKEA, we are creating more opportunities for individuals to earn a consistent, meaningful income on their terms by establishing enduring relationships with clients in communities globally.Taskrabbit operates as a hybrid company, with team members located across the US and EU, and has been recognized as a Built In — Best Places to Work for 2022, 2023, and 2024, receiving accolades across various national and regional categories. Join us at Taskrabbit, where your contributions will be significant, your ideas appreciated, and your potential maximized!This position operates on a hybrid schedule, requiring two days of in-office collaboration per week. It can be based in our San Francisco office or our new New York City office (opening March 2026).About the RoleMachine Learning is a foundational element at Taskrabbit, and we are in search of an experienced Senior Machine Learning Engineer to join our team and help mold the future of ML/AI at Taskrabbit. This distinct, full-stack role is designed for someone who is enthusiastic about the entire machine learning lifecycle—from initial research and model development to constructing the robust infrastructure necessary for deploying and scaling your innovations.As a Senior Machine Learning Engineer, you will engage with exciting challenges that directly influence how users discover and interact with home services on the Taskrabbit platform. You will play a vital role in enhancing our capabilities in areas such as search ranking, content discovery, and recommendation systems. Collaborating closely with data scientists and fellow engineers, you will design and implement cutting-edge algorithms, ensuring the scalability, reliability, and optimization of our models in production alongside software engineers.

About VSCO At VSCO, we empower photographers with an innovative platform that provides essential tools, a vibrant community, and the visibility needed for creative and professional growth. We cultivate an authentic creative environment that welcomes photographers of all skill levels, offering a space that inspires opportunity, collaboration, and connection. Our mission is to support photographers in their journeys, enabling them to thrive and connect with fellow creatives and businesses through our comprehensive suite of tools, available on both mobile and desktop. We seek individuals who are passionate and proactive in advancing our mission. Our team members have the opportunity to make a significant impact, and we believe that collaborative efforts yield stronger results. Our core values are essential to our team culture and guide our hiring process. Learn more about what you can expect when joining VSCO on our Careers Page. About The Role As a Senior Machine Learning Engineer, you will harness the power of AI and machine learning to create innovative, reliable user-facing product features. You will leverage your extensive technical background and hands-on experience in deploying machine learning models to deliver impactful solutions based on real-world feedback. Your focus on measurable outcomes and customer satisfaction drives your work, blending innovation with practical implementation. You will be highly skilled in Python and adept across the data and machine learning stack, enabling you to develop and launch models efficiently while ensuring scalability and maintainability. Whether working with traditional algorithms or cutting-edge deep learning and generative AI, you will expertly navigate the complexity of each problem, managing every phase from defining the challenge to deployment and iterative improvement. Your dedication to software engineering excellence will inform your thoughtful approach to system design for machine learning, encompassing data quality, pipeline design, feature workflows, model serving, and ongoing monitoring and enhancement. By integrating machine learning deeply within our cohesive product experiences, you will collaborate effectively with cross-functional teams, aligning on objectives, defining success metrics, and driving meaningful outcomes. You will stay informed about the rapidly evolving AI landscape, maintaining a discerning perspective that allows your team to focus on significant advancements while avoiding distractions. The Day to Day Design and implement ML-powered features for search, discovery, personalization, and more.

Join Ando Technologies as a Machine Learning Engineer specializing in AI-native systems and forecasting. In this role, you will leverage cutting-edge machine learning algorithms to develop predictive models and enhance our AI-driven solutions. Collaborate with cross-functional teams to transform data into actionable insights and drive strategic decisions. Ideal candidates will have a passion for innovation and a strong understanding of AI technologies.

Join Orchard as a Machine Learning Engineer and play a pivotal role in transforming data into actionable insights. In this dynamic position, you will leverage your expertise in machine learning algorithms and data analysis to develop innovative solutions that enhance our products and services.We are looking for a proactive team player who thrives in a fast-paced environment and possesses strong problem-solving skills. You will collaborate with cross-functional teams, engage with large datasets, and contribute to the design and implementation of machine learning models.

About the Role Waymo is looking for a Senior Machine Learning Engineer focused on Prediction & Planning to join the System Architecture team. This position is based in Mountain View, CA, San Francisco, CA, or New York City, NY. What You Will Do Design and implement advanced machine learning algorithms for autonomous vehicle prediction and planning. Develop systems that improve the safety and efficiency of self-driving technology. Collaborate with engineers and researchers across teams to advance core capabilities in autonomous driving. Impact Your work will help shape the systems that guide Waymo’s vehicles, supporting safer and more reliable autonomous transportation.