Intern Applied Ai Solution Consulting Jobs

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team As an Intern in Applied AI Solution Consulting you join our Value Engineering team to focus on driving and closing opportunities by identifying and selling the value Celonis can bring to customers. Our Value Engineers (VE) are the trusted advisor for customers and work on the intersection of technology and business. VEs don't just understand code; they understand the entire architecture of a deal. By bridging the gap between deep technical capability, customer pain points, and revenue mechanics, it stands out as one of the most high-impact roles in tech. The Role As a VE Working Student, you will sit at the intersection of data engineering, process intelligence, and business strategy. You won't just support the team; you will actively build data-driven solutions within the Celonis Process Intelligence Platform to uncover hidden inefficiencies for companies across the Italian market. This is a highly analytical role where you will translate complex business challenges into technical requirements, using SQL/PQL, data modeling, and AI capabilities to transform raw data into million-dollar business cases The work you’ll do Mine & Model Data: Use the Celonis platform to analyze complex business processes, exposing hidden ine

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location F10NX Department Probe Project Title Move Table Optimizer: Applied Artificial Intelligence for Wafer Test Optimization Project Description Develop an applied Artificial Intelligence solution that automatically generates optimized wafer test movement configurations. During wafer testing, a probe card moves across the wafer to contact and test each die. The movement sequence must cover all required dies using as few contacts as possible. This represents a constrained coverage and sequencing problem that is currently optimized manually on a case-by-case basis. The intern will apply optimization, machine learning, and software engineering techniques to develop an optimization engine and a web application for engineers to visualize, compare, and evaluate recommended configurations. The project provides practical exposure to Artificial Intelligence-enabled optimization, web application development, and semiconductor wafer probe testing. Objective of the Project Develop an optimization engine that generates and ranks wafer test movement configurations. Reduce the manual effort required to evaluate individual wafer test cases. Enable engineers to visualize a

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! The AI Research team at Figma is working on the cutting edge of AI and Design. We work on optimizing agentic systems for design quality and end user experience. We build robust evaluators for Design and post-train models. We are a very collaborative, close-knit and impact-focused team of researchers and research engineers working on some of the most challenging technical problems at the intersection of AI and creativity. We are seeking PhD interns with expertise in machine learning and artificial intelligence to develop innovative AI solutions for design and creative products. Through both fundamental and applied research, your work will contribute to new AI-driven features in Figma products. This internship can take place in Winter 2027 or Summer 2027 in San Francisco or New York. What you’ll do at Figma: Drive fundamental and applied research in Generative AI with Figma product use cases in mind Formulate and implement new modeling approaches both to improve the effectiveness of Figma’s current AI models as well as enable the launch of entirely new AI-powered product features Explore the boundaries of what is possible with the current technology set and experiment with novel ideas Depending on your project, you may have the opportunity to publish your research in leading AI/ML conferences We'd love to hear from you if you have: Are a 4th or 5th year senior Ph.D student in AI, Machine Learning, Computer Vision, Natural Language Processing, Human Computer Interaction or a related field Pro

As an Applied Science Intern, you will join a cross-functional team of engineers and applied scientists building AI-powered features within the Datadog platform. You will contribute to both existing and new products by improving machine learning models, developing new AI capabilities, and helping bring research into production. Working closely with engineering and product partners, you'll gain hands-on experience deploying AI systems at scale while strengthening your product mindset, collaboration, and communication skills. You'll also have opportunities to contribute to cutting-edge research that directly powers customer-facing features. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design solutions for AI use cases by researching and benchmarking state-of-the-art models to identify the best approach Build highly scalable product features using generative AI, machine learning algorithms, and statistical techniques Contribute to the development, deployment, monitoring, and maintenance of production AI models, services, and infrastructure Explore, analyze, and derive insights from the large-scale observability data flowing through Datadog systems Participate in technical knowledge sharing by presenting recent academic research and investigating emerging model architectures to improve existing and future products Collaborate with engineering and product teams to productionize AI solutions and deliver customer-facing features Who You Are: You will graduate in 2027 with a degree in Machine Learning, Artificial Intelligence, Statistics, Computer Science, or a related field You have experience building machine learning models through coursework, research, internships, or personal projects You have strong programming skills and are eager to lear

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

About Us SharkNinja is a global product design and technology company, with a diversified portfolio of 5-star rated lifestyle solutions that positively impact people’s lives in homes around the world. Powered by two trusted, global brands, Shark and Ninja , the company has a proven track record of bringing disruptive innovation to market and developing one consumer product after another has allowed SharkNinja to enter multiple product categories, driving significant growth and market share gains. Headquartered in Needham, Massachusetts with more than 4,100 associates, the company’s products are sold at key retailers, online and offline, and through distributors around the world. AI at SharkNinja At SharkNinja, we’re building an AI-native culture. We’re not waiting for the future; we’re creating it. Our people are expected to experiment boldly, adopt new tools, and continuously raise what’s possible to create meaningful impact for our consumers. If you believe the best way to do your job hasn’t been invented yet, you’ll fit right in. Join the SharkNinja Early Edge Experience: Built for early career talent. Geared toward impact. Driven by speed. Whether you're in a co-op or internship, our early talent program is designed to provide valuable exposure to the industry and a fast-paced professional environment. You'll dive into meaningful projects and tasks that sharpen your skills and deepen your knowledge. Along the way, you'll benefit from professional development opportunities, community events, and connections that make your experience well-rounded and enriching. Your time with us will culminate in an opportunity to showcase your contributions and learnings to SharkNinja leaders because this is a program for those ready to shape what's next — fast. This role: SharkByte is SharkNinja’s AI-native early talent program, designed for builders who want to learn by doing, move fast, and see t

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location Singapore Fab 10N Department Facilities Engineering, Artificial Intelligence and Smart Facilities Project Title Fab 10N Facilities Artificial Intelligence and Workflow Transformation Project Description This internship provides an opportunity to explore the application of Artificial Intelligence, Machine Learning, data analytics, automation, and digital technologies within a semiconductor manufacturing facilities environment. The project focuses on developing AI-Enabled solutions that enhance equipment reliability, predictive analytics capabilities, operational efficiency, knowledge accessibility, and engineering decision-making. The intern will gain exposure to real-world industrial datasets, engineering workflows, Artificial Intelligence technologies, and digital transformation initiatives. Through collaboration with Facilities engineers and domain experts, the intern will learn how advanced analytics and Artificial Intelligence can be applied to solve operational challenges and create business value. Objective of the Project Develop AI-Enabled solutions that improve Facilities Engineering analytics and decision-making. Apply Machine Learning and data anal

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role The Applied Science team builds models and tools that solve Ramp’s most critical problems: from underwriting businesses to combatting fraud to making spend management smarter. We’re deeply embedded in the business and provide a quantitative foundation for decision making. As an Applied Science intern, you’ll be a fully integrated member of the team and own your project from start to finish. Working with engineers, product managers, and business stakeholders, you’ll translate complex business needs into scalable machine-learning-driven solutions. This is a chance to apply ML concretely, ship code, and create genuine value for Ramp and our customers. You will focus on exciting problems in areas like: credit, fraud, growth, or our core product. What You’ll Do End-to-End ML : own the model lifecycle from data exploration and feature engineering to training, benchmarking, deployment, and monitoring State-of-the-Art AI : leverage the latest Large Language Models (LLMs) to solve novel problems and create new product capabilities for our cust

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Role Overview This internship project is designed to provide students with hands‑on learning exposure to data analytics, machine learning, and statistical modeling applied within Process Integration (PI) for advanced NAND technology development. The intern will work on a defined project focused on exploring how data‑driven approaches can support process learning, experimentation, and engineering decision‑making. Through this project, the intern will gain exposure to process, inline, and electrical datasets, and learn how analytical insights can be translated into prototypes, analyses, and documented learnings relevant to PI engineers. Key Responsibilities Build and evaluate data ‑driven models to support PI outcomes such as cycle‑time reduction, faster learning loops, and process optimization. Perform statistical analysis of split experiments (e.g., DOE‑related analysis), including data preparation, feature engineering, and model interpretation. Conduct split-DOE and conversion analytics , including datamining and statistical evaluation of split outcomes (e.g., ANOVA‑style learning). Identify opportunities to accelerate process learning</

Eulerity is a rapidly growing technology company revolutionizing marketing automation for small businesses and franchises with our industry-leading proprietary software. We were founded by leaders from Google, Facebook and Yahoo! with more than 20 years of digital advertising, engineering and marketing experience. Your Role: Take an active role in developing, testing, and maintaining our backend services — leveraging AI agents to accelerate and improve your work Implementing new features, starting from design to deployment Help come up with new features and product ideas, using AI tooling to prototype and iterate quickly Collaborate with other teams on features and releases Assist with the preparation of documentation, training, and support of various systems About You: You have at least hands-on experience working with AI agents (e.g. Claude, Copilot, Cursor, or similar coding agents) to build, debug, and improve software Experience with LLMs, AI agent frameworks, or AI-assisted product development (you've actually used these, not just read about them) At least 1 year of experience building backend solutions with Java You have a strong willingness to continuously learn, experiment with, and deepen your knowledge of AI tools and how they can be applied to real engineering challenges You understand how to use agents and LLMs to find the right resources, generate and review code, and solve problems more effectively You enjoy coming up with creative solutions to complex problems Comfortable integrating with third-party APIs Able to work in conjunction with other team members Great communication skills and a friendly disposition Requirements: Based in the NYC tri-state area Able to commit minimum 20 hours per week Benefits: Pay $18-$20/hour Mentorship with regular peer review sessions Unlimited snacks and an in office lunch credit. Full GitHub Copilot access with frontier LLMs and coding agents from Anthropic, Google, and OpenAI — keeping you equipped with the best AI t

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location MSB, Singapore (990 Bendemeer Road, Singapore 339942) Department New Product Manufacturing Project Title AI-Enabled Manufacturing Analytics and Productivity Automation Project Description The intern will undertake a structured project that applies Artificial Intelligence, Generative AI, data analytics, and automation technologies to selected opportunities within New Product Manufacturing. Under the guidance of experienced engineers and business stakeholders, the intern will evaluate defined processes where AI-Enabled solutions may reduce manual effort, improve data visibility, automate reporting, and generate actionable insights from manufacturing and operational data. The project may involve automated work-in-process reporting, lot-prioritization analysis, intelligent dashboards, or productivity automation. The intern will gain practical experience using approved tools such as Microsoft Copilot, Power BI, Power Automate, Power Apps, SharePoint, Python, and Structured Query Language. Objective of the Project Develop an understanding of New Product Manufacturing processes, data sources, and operational challenges. Identify a defined opportunity where AI, Generative AI, data analytics

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

Team: Apollo — Block Applied R&D Location: Remote (US / Canada) Duration: Fall/Winter 2026 co-op — 8 months, flexible start September 2026 Level: Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads Block's efforts to build the Customer World Model (CWM) : a continuously evolving representation of each customer's goals, context, history, constraints, and likely future needs. The CWM powers proactive intelligence across Block's ecosystem. Instead of customers navigating products in search of features, intelligence observes their world, understands what matters, anticipates what comes next, and initiates actions on their behalf. We believe the next generation of AI products will not be defined by chat interfaces or isolated agents. They will be defined by rich world models that enable systems to reason over a customer's evolving state, make better decisions, and learn continuously from outcomes. Apollo designs, prototypes, and guides the development of this intelligence layer. About the role We're hiring a small cohort of graduate research interns to help build the foundations of proactive intelligence. This is not a traditional internship. You'll own a research problem end-to-end: framing the question, developing methods, running experiments, publishing findings, and, when successful, shipping your work into production systems used by millions of customers and sellers. You'll work at the intersection of representation learning, foundation models, reinforcement learning, causal reasoning, agentic systems, and product intelligence. The goal is not simply to build smarter models, but to build systems that develop a deeper understanding of customers and use that understanding to make better decisions over time. Past interns have shipped production systems within months and published their work in the same year. What you'll work on Depending on your interests and Apollo's roadmap, you'll focus on one or more of the followin

Team: Apollo — Block Applied R&D Location: Remote (US / Canada) Duration: Fall/Winter 2026 co-op — 8 months, flexible start September 2026 Level: Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads Block's efforts to build the Customer World Model (CWM) : a continuously evolving representation of each customer's goals, context, history, constraints, and likely future needs. The CWM powers proactive intelligence across Block's ecosystem. Instead of customers navigating products in search of features, intelligence observes their world, understands what matters, anticipates what comes next, and initiates actions on their behalf. We believe the next generation of AI products will not be defined by chat interfaces or isolated agents. They will be defined by rich world models that enable systems to reason over a customer's evolving state, make better decisions, and learn continuously from outcomes. Apollo designs, prototypes, and guides the development of this intelligence layer. About the role We're hiring a small cohort of graduate research interns to help build the foundations of proactive intelligence. This is not a traditional internship. You'll own a research problem end-to-end: framing the question, developing methods, running experiments, publishing findings, and, when successful, shipping your work into production systems used by millions of customers and sellers. You'll work at the intersection of representation learning, foundation models, reinforcement learning, causal reasoning, agentic systems, and product intelligence. The goal is not simply to build smarter models, but to build systems that develop a deeper understanding of customers and use that understanding to make better decisions over time. Past interns have shipped production systems within months and published their work in the same year. What you'll work on Depending on your interests and Apollo's roadmap, you'll focus on one or more of the followin

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