PhD University Grad Machine Learning Engineer (USA)

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 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 . We’re looking for Data Science interns to help evolve and shape the future of our product -- inspiring Pinners and connecting them with actionable content, understanding advertisers and measuring the value Pinterest provides to them, and enabling our employees to evaluate potential product changes faster than ever before. You’ll apply quantitative analysis, statistical techniques, modeling and data mining while working cross-functionally with engineering and product partners. The results of your work will influence the team roadmap, identify actionable product opportunities, refine our experimentation platform, and drive key initiatives, turning your insights and analyses into real-world products. Note to applicants: By applying to this role, you will be considered for multiple intern roles open across our various DS teams. Please only app

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 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 . With more than 640 million users around the world and 300 billion ideas saved, Pinterest Machine Learning interns help build personalized experiences to help Pinners create a life they love. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else. As a machine learning intern at Pinterest, you'll work on tackling new challenges in machine learning and artificial intelligence. You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: image recognition, user modeling, recommender systems,search, ads, ranking, natural language processing, neural networks, personalization, graph representation learning, and

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. You can learn more about our vision for AI/ML at Sigma in our blog post . That’s where you come in. As an AI/ML PhD Intern , you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. We're looking for PhD students that are passionate about the intersection of AI, business, and data. What You’ll Do Conduct original AI/ML research in search, recommendations, natural language processing, agentic workflows and more Prototype and productionize AI systems that feel intuitive but do a lot under the hood Tackle novel UX problems at the intersection of AI, analytics, and data apps Contribute to the development of scalable AI/ML infrastructure for experimentation, training, and evaluation of large-scale models. What You Bring Current PhD student studying AI/ML at a U.S. accredited university Deep understanding of machine learning, including deep learning algorithms, model architectures and optimization Baseline understanding of building and deploying production-grade AI/ML systems Knowledge of the full ML lifecycle: data curation, training, deployment, monitoring Desire to bridge research and application—bringing new AI ideas from concept to impactful deployment. Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You’ve fine-tuned or trained foundation models (language or multimodal) for novel domains You know your way around cloud infrastru

About the role We are building a higher education researcher motion that helps funded labs adopt OpenAI across core research workflows. This role will develop relationships with principal investigators, researchers, research software engineers, research computing teams, and university technology leaders, then translate high-value use cases into sustained Pro, Codex, API, and ChatGPT Edu usage. This is a hybrid business development and program management role. You will identify and qualify priority labs, design phased access and fellows programs, run pilots, remove technical and institutional blockers, and create repeatable paths from individual researchers to lab- and institution-level adoption. Additionally, this role will launch and manage a community of researchers with events, communications and support. In this role, you will: Build a pipeline of funded labs, research centers, and technical champions at priority R1 universities; qualify opportunities based on workflow value, funding path, influence, and expansion potential. Run discovery with researchers and university stakeholders to understand workflows, data and security needs, procurement constraints, and success criteria. Design and operate phased access and fellows programs, including eligibility, selection, offer mechanics, onboarding, office hours, community programming, and pilot goals. Translate research workflows into effective use of Pro, Codex, API, and ChatGPT Edu in partnership with Solutions, Product, and Education account teams. Manage pilots end to end, remove trust, funding, and technical blockers, and drive measurable activation, retention, and expansion. Turn early usage into product feedback, workflow documentation, peer proof, case studies, and repeatable enablement. Build clear handoffs and expansion paths from researcher to lab to institution; track fellow selection, activation, retained usage, workflow proof, conversion, and expansion. You might thrive in this role if you: Relevant exp

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with petabyte-scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. As a PhD Machine Learning Engineer Intern on our Applied AI team, you'll take on an open research problem tied to product experiences used by millions of riders. Working closely with a Staff ML Engineer mentor, you'll scope the problem, develop and evaluate new methods on real data, and take the work far enough that it can be shared with the research community, with the goal of a paper submission to a top ML venue. If you are a PhD student who enjoys turning open-ended research questions into working systems, and you want your research to be tested against real users and real data, this opportunity is for you! Responsibilities: Own a research project from start to finish: frame the problem, review related work, propose new methods, and design rigorous offline and online evaluations Design, build, train and test ML models in areas such as reinforcement learning, sequential decision-making, personalization Write production-quality code that turns research prototypes into working pipelines on Lyft's data and ML infrastructure Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame research questions within the business context Analyze experimental and observational data, and communicate findings clearly to both technical and non-technical aud

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Lyft Rider Science team is seeking an Applied Scientist intern to develop next-generation user simulation methods using state of the art AI methods. The goal of this project is to develop and validate LLM-based Rider Agents that can serve as behavioral proxies for real riders, and study when agent simulations can provide reliable signal about rider responses to product interventions before online experimentation. You will build agent-based simulation systems grounded in real rider context and behavioral data, evaluate their fidelity against observed rider behavior and historical experiments, and study where these simulations can accelerate product iteration and experimentation. This role combines LLM engineering, agent-based modeling, machine learning, and causal inference with direct applications to real-world rider products. The expected outcome is to build a working Rider Agent simulation prototype, establish an evaluation framework for measuring simulation fidelity and validate the framework using historical rider experiments. Responsibilities: Develop LLM-based Rider Agents that represent heterogeneous rider contexts, preferences, histories, and behaviors Build agent-based simulation environments for evaluating rider interactions with different product experiences and interventions Build evaluation pipelines to assess realism, robustness, and mechanism plausibility of simulated behavior against human data or established theory Analyze emergent behaviors and interaction dynamics in simulated populations under different user segment and marketplace conditions Conduct experiments and ablation studies on agent behavior, interaction dynamics, and simulation validity Apply the simulation framework to real Rider product problems and assess its usefulness for hypothesis generation, product iteration