Ai Research Intern Jobs

About Paytm Europe Merchants deserve better from their payments provider: fairer pricing, faster settlement, easier tools, and support from a partner that understands their business. Paytm Europe Payments S.A., backed by One97 Communications Limited, one of India's largest fintech groups, is building a merchant payments business in Europe. We are starting with Luxembourg and are currently in the early stages of shaping our product, go-to-market approach, merchant outreach, and local market understanding. We are looking for motivated interns who are curious, proactive, and excited to be part of building something from the ground up. About the Internship Duration: 6 months Location: Luxembourg Type: Internship As a Market Intelligence Intern, you will help Paytm Europe better understand Luxembourg's merchant market: visiting local businesses, speaking with merchants, collecting information on how they accept payments today, and helping the team spot opportunities. This is a hands-on role, split between the field visits and desk research. What You'll Be Doing ● Visit merchants across Luxembourg: restaurants, cafés, retail shops, convenience stores, fuel stations, and other small businesses. ● Ask merchants how they currently accept payments, which provider or card machine they use, and what works well and what does not. ● Record findings in a structured format: merchant name, location, business type, payment method, provider, and key pain points. ● Support desk research on Luxembourg's payments market: local providers, pricing models, card machines, and merchant reviews. ● Identify common challenges: payment costs, settlement delays, onboarding friction, hardware or reporting issues. ● Explore where AI or tech tools could help merchants: marketing, invoicing, inventory, reporting, loyalty, scheduling. ● Write findings into simple weekly summaries for the team. ● Coverage areas: Luxembourg City, Kirchberg, Cloche d'Or, Esch-sur-Alzette, Differdange, Dude

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it’s medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity . Are you looking to be an AI & SAAS Support Intern on a growing team? If so, this may be the role for you! You will be the face of FourKites to our customers—their main point of contact for everything they need. From helping customers track urgent shipments to providing assistance to carriers hauling the loads, you will be the product expert and go-to person to help users when they reach out. This internship is designed for hands-on, experiential learning —you'll get real exposure to how a growing SaaS platform operates, paired with the chance to work on special AI projects alongside our product and engineering teams. What you'll be doing: First point of contact for FourKites customers, partners & consultants to research, troubleshoot, replicate, and test product problems and bugs Track issue progress and provide regular updates to clients until incidents are resolved Interface with Development, QA, and Consulting Services as needed to resolve customer issues Contribute to special AI-driven initiatives , applying a curious, experimental mindset to explore how AI can improve support workflows and customer outcomes Be part of weekend rotation for 24/7 customer emergencies About the team: Our product and engineering teams are dedicated to providing the industry's best-in-class end-to-end supply chain visibility platform. We are committed to building a high-performing team with software craftsman-thinking who are dedicated to developing and enhancing our core platform, and we want you to be a central part of it! We help companies transform their end-to-end supply chain with real-

At Dscout, we’re building the most flexible and powerful UX research platform on the market—trusted by the world’s top brands in finance (JP Morgan Chase, Intuit, Charles Schwab, PayPal), healthcare (Aya, Headspace), consumer goods (Keen, Verizon, Target, Northface), and tech (Google, Amazon, Facebook, Meta, Spotify, AirBnB). Our tools help teams deeply understand the humans behind their products, so they can build better ones. We are expanding our smart and driven team and would love for you to join us. We are looking for a Research Advisor to join our growing Customer Experience and Research (CXR) team. In this position, you will work collaboratively with Lead Research Advisors and Dscout clients to help our customers use our platform to design, recruit and field research projects. Our clients conduct research on a wide range of topics varying across: technology, retail, healthcare, and AI, just to name a few. You will have a chance to make a real difference for Dscout’s customers and build your career in the worlds of research and customer success. You are an incredible communicator and a genuine, creative problem-solver. You’re the client’s partner in learning a new digital tool to execute powerful research. You collaborate with clients as they develop research plans, and help to identify Dscout methodologies that best meet their needs. Internally, you are our clients’ champion to drive larger improvements to the platform and overall user experience. The Research Advisor position is among the most central to Dscout’s operations, and means you’ll work with people from across the company on a regular basis, especially our product, engineering and sales teams. If this sounds exciting to you, apply today! What you will do: Act as a true Dscout expert to train and educate clients on features and functionalities Provide specific recommendations for clients’ research design on Dscout Assist in running clients’ research projects on Dscout in

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. Micron’s Chemistry Lab plays a critical role in advancing semiconductor technology by developing analytical methods that support materials understanding, process development, defect characterization, and next-generation memory innovation. The team applies advanced chemical, optical, and surface characterization techniques to solve complex materials challenges across semiconductor manufacturing and research. We are seeking a highly motivated summer intern to contribute to advanced spectroscopy and nanoscale characterization projects focused on semiconductor thin films, surfaces, interfaces, and process-induced material changes. Working alongside scientists and engineers in Corporate Labs, the intern will develop and apply spectroscopy-based characterization methods, analyze complex materials datasets, and gain experience in experimental design, data analytics, and semiconductor materials research within an industrial laboratory environment. Responsibilities Conduct experiments using advanced spectroscopy and microscopy techniques to characterize semiconductor thin films, surfaces, interfaces, and related materials. Collect, process, analyze, and interpret spectroscopy data, including photoluminescence, fluorescence lifetime, Raman, and AFM-IR datasets, and develop visualization workflows to communicate results. Correlate spectroscopic signatures with material properties, process conditions, surface states, and defect behavior while colla

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. Would you like to work in one of the most complex Fab environments in the world? As an industrial engineering intern in our research and development factory you will work on projects that further optimize our very automated factory. This role will provide exposure to larger data sets than you have ever worked with and will challenge your data management skills. Not only will this role significantly grow your skills but will also provide exceptional value to the organization on a real issue in our factory! Responsibilities: Identify key performance indicators for R&D program success. Use large data sources to extract and analyze planning data. Build reporting in Tableau and other systems to convey data to program teams. Construct infographics that display key information in easy-to-understand formats. Leveraging AI tools and find new ways to apply AI in the workplace. Minimum Qualifications: Working towards completion of a Bachelor’s or Master’s degree in the following areas: industrial engineering, manufacturing engineering, supply chain, Operations or other related discipline with expected graduation after this internship timeframe Must be a current student, and cannot graduate prior to September 2027. Ability to code in SQL, Python or similar to execute data extraction. Effective with Excel, Tableau or other data management and visualization software. Preferred Qualifications: Skille

Salary range - $250k - $350k | Equity - up to 0.5% | In-person NYC About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We’re at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, Chandra, Surya, Marker, and Lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview We're looking for a Research Engineer to own problems end to end across our models, inference service, and product. You won't just train a model and hand it off. You'll take it from training through benchmarking, into our inference stack, and work with the team to integrate it into our products. We're a small team that has shipped the current state of the art OCR model, Chandra. Our models collectively have 70k+ Github stars. Our tools are used internally at frontier AI labs like Anthropic, and Fortune 500 enterprises like Siemens. Our team focuses on training small, efficient models that outperform much larger LLMs on domain-specific tasks (like OCR, structured extraction, tables). We move fast, prioritize practical results, and build tools that are open, reproducible, and built to last. You'll test hypotheses quickly, iterate on results, and balance experimental rigor with shipping to customers. Day to day: A typical project might look like: identify a gap in extraction quality on long documents, train and benchmark a new model, optimize it for inference, and work with the team to ship it to users. Concretely: Train and evaluate models: Train task-

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team You'll work closely with several teams of engineers and PMs to shape products used by Stripe employees across engineering, operations, finance, and beyond. This is a high-impact role for a designer who finds as much satisfaction in untangling complex workflows and dense information architectures as in crafting polished interfaces. What you'll do You'll take ownership of two spaces within our internal tooling portfolio—Developer Productivity, focused on ensuring every engineer at Stripe has the tools to be productive, and Collaboration, focused on knowledge discovery and communication at scale. You'll pair with an existing designer on the team to bring design quality and consistency to surfaces that are critical to how Stripe operates internally. Responsibilities Own end-to-end design for a portfolio of internal tools—from discovery and problem framing through interaction design, prototyping, and implementation support Partner with engineering and product managers to define product requirements and translate them into clear, usable, and well-considered design solutions Conduct lightweight research and usability sessions with internal users to validate decisions and surface unmet needs Contribute to a consistent design language across our internal tools suite, working in close coordination with the Sail Design team and the Stripe design system Make design trade-offs confidently, knowing when to go deep on craft and when to ship a pragmatic sol

About the Team The Product Policy team is responsible for the development, implementation, enforcement, and communication of the policies that govern use of OpenAI’s services, including ChatGPT, GPTs, the GPT Store, Codex, and the OpenAI API. About the Role We are looking for a Research and Advisory Partnerships Lead to build and manage the relationships, partnerships, and advisory structures that bring independent external expertise into our product and policy decisions. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will identify and engage researchers, civil society organizations, subject-matter experts, and other external stakeholders whose perspectives can strengthen how we develop and deploy AI. You will establish and manage advisory councils, develop research partnerships with the academic community, and work closely with internal teams to translate external insights into actionable guidance. This role sits at the intersection of product, policy, research, and governance. It is well suited to someone who is comfortable building relationships across disciplines and designing processes that ensure outside expertise meaningfully informs internal decision-making. This role can be based in San Francisco or New York City. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Develop, launch, and manage external advisory councils and other governance mechanisms that provide structured input on product and product policy. Build and maintain relationships with external experts, researchers, civil society organizations, and other stakeholders who can inform high-priority product and product policy decisions. Identify when external consultation can improve internal decision-making, and develop engagement strategies tailored to specific products, policy questions, and emer

About the Team OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort. The Human Data engineering team creates the systems that enable scalable, high-quality human feedback. These systems are essential to how OpenAI trains and improves its most advanced models. Engineers on this team collaborate closely with world-class researchers to bring alignment techniques to life — from experimental ideas to production-ready feedback loops. About the Role We’re looking for software engineers to join the Human Data team and build the platforms, prototypes, tools, and infrastructure that power how our AI models are trained, aligned, and evaluated. You’ll partner with researchers and cross-functional teams to bring alignment ideas to life, influence future model training, and shape how models interact with the real world. We’re looking for people who are excited by technical ownership, enjoy working across the stack, and are eager to solve ambiguous problems in a high-impact, fast-paced environment. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Build and maintain robust full-stack systems for feedback collection, data labeling, and evaluation pipelines, while maintaining high levels of security. Translate experimental alignment research into scalable production infrastructure, including inference and model training stacks. Design and iterate on user-facing tools and backend services to support high-quality data workflows Partner with researchers, engineers, and program leads to shape feedback loops and model interaction paradigms Drive infrastructure improvements that enable faster iteration and scaling across OpenAI’s frontier models, from internal r

JLL empowers you to shape a brighter way . Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Research Analyst – JLL What this job involves: The Research Analyst will join JLL's San Francisco Research team to deliver market intelligence that sets JLL apart. You will analyze San Francisco's industrial, office, and flex markets alongside the economic drivers that shape them. This role combines direct client engagement with hands-on data analysis, positioning you at the intersection of urban economics and commercial real estate. You will grow from foundational market research into automated workflows, quantitative modeling, and independent analysis—building both analytical rigor and technical capability. If you're curious about what drives markets and ready to become data fluent while mastering local real estate dynamics, this role offers a clear path forward. What your day-to-day will look like: Develop expertise on San Francisco's economy, industry composition, demographics, and commercial real estate market to identify trends and emerging opportunities Maintain comprehensive market coverage by tracking significant leasing activity, tenant movements, development projects, sales transactions, and ownership changes Meet regularly with clients and internal teams to present market insights, conditions, and forecasts Produce quarterly reports on San Francisco market

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. The Realtime Defect Analysis (RDA) Yield Technology team supports advanced DRAM research and development by identifying, analyzing, and reducing manufacturing defects that impact yield and product performance. The team partners closely with engineers across R&D and High Volume Manufacturing to improve process stability, accelerate learning cycles, and drive continuous improvement through data-driven decision making. As an RDA Yield Technology Intern, you will gain hands-on experience with innovative semiconductor processing, defect inspection systems, and advanced analytical techniques. You will contribute to projects focused on experimentation, defect detection, data analysis, and process optimization while collaborating with multi-functional engineering teams. This role is ideal for individuals who are passionate about problem solving, root-cause investigation, and leverausingology to improve manufacturing performance. Responsibilities Analyze experimental process flows and defect inspection data to identify anomalies, investigate root causes, and support corrective actions. Partner with R&D and manufacturing teams to improve yield performance through defect detection, process monitoring, and continuous improvement initiatives. Leverage Artificial Intelligence (AI) and data analytics tools to accelerate defect detection, identify yield-impacting trends, automate routine analysis workflows, and generate actionable insights. Use inline defect signals, statistical analys

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. The Thin Films Equipment Engineering team at Micron develops and enhances advanced semiconductor manufacturing equipment in a fast-paced research and development environment. The team works closely with Process Engineering, Facilities Engineering, and equipment suppliers to enable next-generation memory technologies and achieve world-class equipment performance. Through innovation, collaboration, and data-driven decision-making, the team plays a critical role in advancing semiconductor technology development. As a Thin Films Equipment Engineering Intern, you will gain hands-on experience working with groundbreaking semiconductor equipment and processes. You will support engineering projects focused on equipment optimization, data analysis, and technology development while collaborating with multi-functional teams. This role provides exposure to semiconductor manufacturing, experimental design, and the application of advanced analytics to solve complex engineering challenges. Responsibilities Collect, analyze, and interpret equipment and process data to find opportunities for performance optimization and continuous improvement. Support structured engineering experiments, document findings, and communicate results through technical reports and presentations. Collaborate with Equipment Engineering, Process Engineering, Facilities Engineering, and equipment suppliers to address technology-development challenges and improve equipment performance. Develop an understanding of equipment hardware,

About the Team OpenAI's Research Data Team exists to accelerate the evaluation, safety and capabilities of our models and products. Made up of technical operators and software engineers, we design the methods in which we acquire and create data. About the Role As a Research Program Manager (RPM), Data Acquisition, you will partner with research, engineering, and operations to design and implement pragmatic solutions for acquiring data. You will be a key interface between our research roadmap and external data offerings. This role is based in our San Francisco HQ and will be part of a team of RPMs pushing the frontier of data acquisition. In this role, you will: Partner deeply with research: Work with researchers to scope data needs, define success criteria, and translate priorities into clear execution plans. Shape the data acquisition pipeline: Identify, evaluate, and advance high impact data opportunities - balancing research value, feasibility, quality, and responsible execution. Unblock yourself: Move work forward even when the path is unclear — using technical judgement, creative problem solving, and scrappy execution to make progress while longer-term solutions are still forming. Build lightweight systems and visibility: Use SQL, Python, dashboards, and simple tooling to track performance, quality, and blockers. Drive technical roadmaps: Collaborate with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management. Scale your impact: Equip vendors and internal teams with the context, standards, and operating rhythms needed to focus on the most important problems. You’ll thrive in this role if you: Are proficient in SQL and Python for analysing datasets, querying databases, building dashboards, and generating actionable insights. Are comfortable using APIs, automation, and AI tools such as Codex to accelerate workflows, remove manual overhead, and upskill quickly in unfamiliar technical areas.Experience sou

About the Team The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. About the Role As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. This position is located in San Francisco. Relocation assistance is available. In this role, you will: Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and prod

About the Team The Future of Computing Research team is an applied research team within the Consumer Devices group focused on developing new methods, models, and evaluation frameworks that support our vision for the future of computing. We work at the frontier of multimodal AI, helping turn emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust. Our work explores a new class of AI systems that can learn over time, adapt to individuals, and support people in the flow of daily life. This includes long-term memory, user modeling, and personalization systems that are aligned not just with immediate satisfaction, but with a person’s broader goals, values, and well-being. We work closely across research, engineering, design, product, and safety to define what it means to build AI systems that know you over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial. About the Role We are looking for a Research Engineer / Scientist to join the Future of Computing Research team to work on RLHF and post-training for personalized, multimodal AI systems. This role will focus on building the learning and evaluation foundations that help models become more context-aware, adaptive, and useful over time. You will work on problems such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that must make high-quality behavioral decisions in realistic user settings. The work is deeply product-grounded: success is not just higher benchmark performance, but better model behavior in real-world use. The ideal candidate is excited about pushing beyond one-turn assistant behavior toward systems that improve through feedback, learn from richer signals, and are trained against meaningful notions of user value. Internally, that maps closely to the need for careful reward design, feedback loops, and evaluation frameworks that test whether i