Systems Phd Jobs

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 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 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 engineers 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. By applying to this role, you will be considered for multiple roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process. This is a general posting for multiple roles open across our various ML teams. You will have the opportunity to work on a very large scope of problems in recommender systems, search, ads, ranking, natural language processing, graph representation learning, personalization, etc. A

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have work

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. We are the team defining the future of memory systems. Our DRAM Architecture organization works at the intersection of silicon, packaging, systems, and customers to build technologies that power next-generation platforms. If you enjoy solving ambiguous problems that matter at industry scale, this is the place. This role is a senior technical leadership position with broad architectural ownership. You will develop complete DRAM system architectures, impact industry direction, and engage directly with customers and executives to convert complex ideas into scalable products. Responsibilities: Define next-generation memory system builds focusing on performance, capacity, RAS, and telemetry Lead cross-stack co-optimization spanning silicon, package, module, board, and system Architect sophisticated RAS and telemetry features and translate system needs into silicon Drive long-range memory technology strategy and influence industry standards Act as a senior technical liaison to customers, executives, and partners Minimum Qualifications: Bachelor’s degree or relevant equivalent experience in EE, CE, CS, or a related field Extensive hands-on experience in DRAM or memory systems architecture Deep understanding of DRAM timing, signaling, power, and reliability mechanisms Proven ability to translate system requirements into silicon architecture Preferred Qualifications: Master’s degree or PhD, or equivalent experience, in a related technical field Recognized techn

Distributed Systems engineers at Datadog design, implement and run in production the foundational platforms powering our applications. Your data pipelines will ingest, store, analyze and query in real-time billions of events per second from companies all over the globe. The platforms are optimized for durability, high availability, low latency, internet-scale footprint and operability. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Build fault-tolerant, horizontally scalable solutions running in multi-tenant environments Write in Go, Java, Rust or C++, amongst other languages Use Kafka, Redis, Cassandra, Elasticsearch and other open-source components Own meaningful parts of our service, have an impact, grow with the company Who You Are: You have a BS/MS/PhD in a scientific field or equivalent experience You have significant backend programming experience in one or more languages (Go, Java, Rust, C++) You have been exposed to working on problems (high durability / low latency /…) You can get down to the low-level when needed You care about simple designs and performance You want to work in a fast, high-growth startup environment that respects its engineers and customers You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how You have demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output Bonus: You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you

Distributed Systems engineers at Datadog design, implement and run in production the foundational platforms powering our applications. Your data pipelines will ingest, store, analyze and query in real-time billions of events per second from companies all over the globe. The platforms are optimized for durability, high availability, low latency, internet-scale footprint and operability. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Build fault-tolerant, horizontally scalable solutions running in multi-tenant environments Write in Go, Java Rust or C++, amongst other languages Use Kafka, Redis, Cassandra, Elasticsearch and other open-source components Own meaningful parts of our service, have an impact, grow with the company Who You Are: 6+ years of experience You have a BS/MS/PhD in a scientific field or equivalent experience You have significant backend programming experience in one or more languages (Go, Java, Rust, C++) You have been exposed to working on problems (high durability / low latency /…) You can get down to the low-level when needed You care about simple designs and performance You want to work in a fast, high-growth startup environment that respects its engineers and customers You have demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output. Bonus: you’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products. This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government. Datadog values peo

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. At Roblox, we believe advanced research belongs in production, driving core algorithmic advances at a global scale. In this role, you’ll own high-impact projects end-to-end, from initial ideation to production deployment and academic publication, while solving complex, high-dimensional challenges at world-scale concurrency. Your expertise, across research areas including Computer Vision and Graphics, multimodality, NLP, or recommendation systems, will directly shape the experience for millions of daily active users. Come build the AI-driven infrastructure powering the future of immersive entertainment. You Will Prototype and implement advanced AI and machine learning solutions that drive core platform features and innovation at scale. Develop and deploy cutting-edge models (e.g., deep learning, generative AI, multimodal architectures) to solve complex, high-impact technical challenges. Collaborate with applied researchers, engineers, and product teams to translate advanced research concepts into production-ready systems. Translate complex research into scalable, robust infrastructure that directly impacts hundreds of millions of daily active users. Work backward from user and product

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. At Roblox, we believe advanced research belongs in production, driving core algorithmic advances at a global scale. Machine Learning is a key growth lever, powering everything from real-time 3D generative AI to complex ecosystem economics across our global platform. As an Applied Scientist - PhD Intern, you’ll be part of a community of curious scientists and engineers building the foundational and applied ML methods at a scale of millions of daily active users and billions of daily AI requests. We combine innovative research—including Computer Vision and Graphics, multimodality, NLP, and recommendation systems—with world scaling distributed engineering. During your 12 or 16 week internship in the Winter, Summer, or Fall, you’ll own a high-impact project from ideation and experimentation to production and publication. There’s also the possibility of continued collaboration beyond your internship, as we support experimentation and production with top researchers, engineers, faculty, and PhD candidates globally that can lead to publications at esteemed venues. You Will Prototype, experiment with, and deploy advanced AI, machine learning, and 3D technologies to solve real-world chal

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! We're looking for a research-minded Data Scientist to join the Core Data team. This team is a group of analytics professionals and Engineers building the foundational platforms for data science at Figma. We build the experimentation, analytics, and AI tooling that every product team relies on to make confident, data-driven decisions, partnering closely with Data Infra, ML, and Applied Science to evolve our platforms and embed AI into the daily workflows of data scientists across the company. This role is for someone who thrives at the intersection of rigorous research and real-world impact. You'll bring PhD-level depth to problems that matter. This includes advancing our experimentation platform and developing machine learning-based analytical systems. You will also help craft how we measure AI-powered features through causal inference and statistical modeling. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Partner across teams to define and track important metrics, develop experiments, and uncover insights that inform strategic decisions Accelerate Figma's experimentation platform and methodology, including A/B testing frameworks and causal inference techniques Construct models and analytical frameworks based on machine learning to support product, platform, and business initiatives Create tools, datasets, and systems that enable others to work with data more efficiently

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

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. At Micron Technology, we transform how the world uses information to enrich life for all. The Heterogeneous Integration Group (HIG) HBM Architecture team develops next-generation High-Bandwidth Memory (HBM) solutions that power AI, high-performance computing, cloud infrastructure, and advanced networking systems. The team works across architecture, design, verification, packaging, product engineering, and technology development to evaluate innovative memory architectures and deliver scalable, high-performance semiconductor solutions. As an HBM Design Architect, New College Graduate, you will contribute to the evaluation and development of future HBM and DRAM architectures. Working with experienced architects and engineering teams, you will analyze system and block-level design tradeoffs related to performance, power, area, thermal behavior, reliability, and manufacturability. This role provides an opportunity to leverage AI, Large Language Models (LLMs), and data-driven engineering methodologies to accelerate architecture exploration and improve decision-making. Responsibilities Analyze HBM and DRAM architectures using analytic

Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are looking for a Lead AI Research Engineer, Embodied Systems to lead and own the engineering of the systems that turn embodied AI into real-world robot behavior. You will be the technical owner and lead for the full embodied systems stack — the onboard AI system, the data collection system, the teleoperation systems, and the on-robot reinforcement learning system — driving the direction hands-on and closing the loop between data, models, and action in the physical world. Responsibilities Lead and own, from the engineering side, the embodied systems that power RoboForce's data flywheel — the onboard AI (inference) system, the data collection system, the teleoperation systems and the on-robot reinforcement learning system. Set the technical direction and architecture for how learned models run, are evaluated, and improve on real robots. Deliver these systems end-to-end on physical robots — from bring-up through reliable, real-time operation in demanding industrial environments. Own on-robot deployment and closed-loop evaluation of policies, turning real-world performance into measurable improvements. Partner with and influence the robotics software team and the ML research team to align interfaces and priorities across the stack. Grow the direction — mentor engineers and raise the technical bar for embodied systems work. Requirements Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or related field with significant relevant experience, or a PhD degree. Track record of leading complex robotic or embodied systems end-to-end and setting technical direction for other engineers. Strong proficiency in both C++ and Python, with solid systems programming and real

We are looking for a Principal Architect for SoC and System performance modelling. The NVIDIA Architecture Modeling group is looking for architects and software developers to join our various architecture efforts. A key part of NVIDIA's strength is to innovate in parallel computing fields, delivering the highest performance in the world for high-performance computing. We are constantly looking for ways to improve our SoC and Systems architecture and maintain our leadership. In this position, you will be working with other world-class architects on modeling, analysis and validation of chip & system architectures and features that advance the state of art in performance and efficiency. What you'll be doing: Modeling and analysis of SoC & Systems algorithms and features Work in a matrixed environment, across the different modelling teams, to document, design, develop tools to analyze and simulate, validate, and verify models Familiarize with the different models (functional and performance) that are used at NVIDIA and help with feature implementation as required. Develop tests, test plans, and testing infrastructure for new architectures/features and code coverage analysis and reporting Mentor early engineers and help sustain good coding practices. Learn about newer modelling techniques and frameworks, evaluate the best solution for our needs and work with your manager to drive the change What we need to see: Bachelor's Degree (or equivalent experience) in a relevant discipline (Computer Science, Electrical Engineering or Computer Engineering) 15+ years of relevant work experience or MS with 12+ years of experience or PhD with 7+ years of experience Strong programming ability: C++, C along with a good understanding of build systems (CMAKE, make), toolchains (GCC, MSVC) and libraries (STL, BOOST)