Machine Learning Intern Co Op Jobs

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors At Nextdoor, machine learning is one of the most important teams we are growing. Machine learning is starting to transform our product through personalization, driving major impact across different parts of our platform including newsfeed, notifications, ads relevance, connections, search, and trust. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. We believe that ML will be an integral part of making Nextdoor valuable to our members. We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior. We are looking for great engineers who believe in the power of the local community to empower our members to make their communities great places to live. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make You will be part of

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About Okta Secures AI Team The Okta for AI Agents Team is building the future of digital identity management. The way companies are using agents and allowing them access is undergoing a fundamental shift, enabling teams to move fast while staying secure. Our North Star is clear: To get AI right, you have to get identity right. We are not just managing identities; we are building the industry's first Identity Security Fabric for the agentic era. As organizations rapidly deploy AI, these non-human entities are acting with access to critical tools, often bypassing traditional perimeters and creating a 'Shadow AI' crisis. Our mission is to move identity from a reactive gatekeeper to a unified control plane, transforming AI risk into business ROI. We are tackling this by implementing a comprehensive four-pillar maturity model: Discover, Onboard, Protect, and Govern. We are driving innovation by defining the standards for Agentic Identity—including pioneer work with securing AI Agents and support for protocols like MCP. You will be helping us build the infrastructure that allows enterprises to scale AI safely, ensuring every access decision—whether made by a human or an automated agent—is authenticated, authorized, and audited at scale. We are a diverse team of engineers, product managers, and designers who are bringing Okta’s expertise in identity to define the future of Agent Identity management, focusing on enablement while staying secure. About the role

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About Okta Secures AI Team The Okta for AI Agents Team is building the future of digital identity management. The way companies are using agents and allowing them access is undergoing a fundamental shift, enabling teams to move fast while staying secure. Our North Star is clear: To get AI right, you have to get identity right. We are not just managing identities; we are building the industry's first Identity Security Fabric for the agentic era. As organizations rapidly deploy AI, these non-human entities are acting with access to critical tools, often bypassing traditional perimeters and creating a 'Shadow AI' crisis. Our mission is to move identity from a reactive gatekeeper to a unified control plane, transforming AI risk into business ROI. We are tackling this by implementing a comprehensive four-pillar maturity model: Discover, Onboard, Protect, and Govern. We are driving innovation by defining the standards for Agentic Identity—including pioneer work with securing AI Agents and support for protocols like MCP. You will be helping us build the infrastructure that allows enterprises to scale AI safely, ensuring every access decision—whether made by a human or an automated agent—is authenticated, authorized, and audited at scale. We are a diverse team of engineers, product managers, and designers who are bringing Okta’s expertise in identity to define the future of Agent Identity management, focusing on enablement while staying secure. About th

About the Team The Ads & Promos Delivery team powers the last-mile delivery of ads and promotions, two marketing products offered to merchants, connecting merchant intent with consumer demand across search and discovery experiences. As a Principal Engineer, you will lead the technical direction for AI-first experiences, including ranking and relevance systems that sit at the core of our ads marketplace and shape how ads are selected, ordered, and personalized in real time across all verticals. You will design and build next-generation AI-first ranking systems using state-of-the-art techniques such as sequence modeling, deep learning, and large language models (LLMs). Your work will span query understanding, user and merchant representation learning, contextual relevance, and multi-objective optimization, balancing advertiser value, consumer experience, and marketplace health at scale. You will set the long-term technical vision, drive cross-team alignment, and translate cutting-edge research into production systems that operate under strict latency, scale, and reliability constraints. As DoorDash expands into 40+ global markets and new verticals such as Grocery and Retail, this role offers a rare opportunity to define how modern AI, including sequential models and LLM-powered decisioning, reshapes ads relevance in a closed-loop marketplace. About the Role Apply state-of-the-art machine learning and LLM techniques to problems across personalization, query understanding, user and content understanding. Rigorously evaluate ML and LLM models using a combination of offline analysis and online experimentation, designing metrics and experiments that clearly measure quality, impact, and tradeoffs. Own the full model lifecycle from research to production, including data analysis, model development, evaluation, offline and online A/B testing, and continuous iteration. Partner closely with product managers, data scientists, and designers to ensure AI-driven systems deliver

The goal of a Staff Machine Learning Engineer at Scale is to lead the design and deployment of agentic AI systems that operate in real-world, mission-critical government environments. On the Public Sector team, you’ll work at the intersection of agentic ML, systems engineering, and applied research, building foundational infrastructure that enables AI systems to reason, plan, and act reliably at national scale. Our Public Sector ML Team partners directly with U.S. defense and intelligence agencies to deploy AI into classified and regulated environments. Through flagship programs like Donovan and Thunderforge , we are advancing the next generation of agentic AI for geospatial reasoning, planning, and decision support. Staff Machine Learning Engineers play a central role in setting technical direction, owning core architectures, and translating ambitious ideas into production systems trusted by government operators. You will: Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability. Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data. Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently. Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets. Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions. Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts. Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments. Partner closely with engineering managers, product leaders, and researchers to scope high-impac

The goal of a Senior Machine Learning Engineer at Scale is to own how we apply generative AI, agentic AI, computer vision, and reinforcement learning to mission-critical problems in production. Our senior machine learning engineers are handed problems that don't yet have an established approach, they propose the architecture, build it with support from other engineers, and are accountable for whether it holds up in the environments our customers depend on. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge . Our work spans multiple modalities, with our primary focus on agentic systems built on large language models. We are developing agents that solve complex operational and planning challenges for government partners: agent frameworks that integrate custom retrieval pipelines and production APIs, memory and context-management systems that hold state across long-running tasks, geospatial reasoning over maps and spatial data, and the evaluation tooling that benchmarks and refines agent behavior. We also apply reinforcement learning in targeted places where it earns its keep, and our computer vision work advances evaluation, labeling efficiency, and multimodal model training in support of defense applications. As a Senior MLE, you'll have design authority over a capability area - the final say on the patterns used within your team, and the responsibility to make those patterns work under real constraints: classified environments, limited compute, and correctness requirements that don't bend. You will: Own the design and delivery of agent capabilities end to end - architecture, implementation, and the evaluation that proves they work Define net-new patterns in problem spaces with no established approach, propose them to the wider team, and lead the work to build them Take state of the art models developed internally and from the commu

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Team : Have you ever considered what powers the intelligent features behind seamless product experiences? The GenAI team is at the forefront of enabling AI-powered security and intelligent innovation across our organization. From crafting AI powered security services, to intuitive generative AI-powered chat experiences that provide instant product support, and developing the best developer experience around authentication for generative AI and AI agents, our team is instrumental in bringing the transformative power of AI to life. We collaborate closely with the Machine Learning team and various product teams to ensure the seamless and secure delivery of AI-enhanced features that provide real value to our users. The Opportunity : As a Staff Machine Learning Engineer on the Generative AI team, you will help shape, architect, and accelerate our Generative AI strategy by contributing across the stack of model development, infrastructure, and platform services. You’ll drive design and implementation of production-ready AI/ML systems at scale: ranging from LLM-powered features to reusable components that other teams across Okta can build on. You will have the opportunity to: Architect, design, and deploy robust Machine Learning & GenAI systems, ensuring seamless integration with diverse platform services and establishing scalable LLMOps pipelines in production. Drive technical decision making while striving to hit the right balance between factors s

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. About the Team The Embedded Insights team supports Plaid’s mission to build a world-class suite of intelligence products. We identify the best opportunities to use machine learning in Plaid products, prove out those opportunities, and collaborate with cross-functional partners to turn them into real-world production systems. About the Role As a Senior Machine Learning Engineer on Embedded Insights, you will help shape Plaid’s future by building machine learning-powered products and features. You will initially support the Plaid App, working on a 0-to-1 consumer-facing product and helping establish product-market fit for a new business line. You will work closely with product managers, data scientists, engineers, customers, and other machine learning engineers to translate ambiguous opportunities into effective ML systems that create measurable customer value. In supporting the Plaid App, you will: Build machine learning-based features for a 0-to-1 consumer-facing product. Partner with product managers to translate ambiguous business requirements into machine learning problems and influence product strategy and roadmap decisions. Rapidly iterate and experiment to help drive product

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role is hybrid requiring 2 days in office at our San Francisco or NYC hub every Tuesday & Wednesday. About the Role Machine Learning is a cornerstone at Taskrabbit, and we’re looking for a Staff Machine Learning Engineer to take technical ownership of our core ranking system. Every job request on the platform flows through it, making this one of the most consequential ML systems we run. This is a hands-on technical leadership role. You’ll operate as the primary architect and engineer for the ranking system — defining the system direction, driving the roadmap, solving the hardest problems, and creating leverage for the engineers around you. You’ll also serve as the primary technical interface for Product, Data Science, Risk, and Commerce on all things matching. What we need is a single technical owner who can hold the architecture, translate strategy into engineering action, and mentor the team as the system scales. Wha

Senior: PLN 260,400 - 352,200 Staff: PLN 350,700 - 474,400 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level About Graphcore At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence Job Summary As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field. The Team The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Location Requirement This is a hybrid role based in Copenhagen, Denmark. Candidates must currently reside in Denmark or be willing to relocate independently, as relocation support is not provided for this position. About Open Intelligence We are the Activation arm of WPP Open Intelligence. Open Intelligence is a highly strategic initiative at the intersection of data science, advertising technology, and audience insights. Our team is building the data and ML systems that power the next generation of marketing and media intelligence, deeply integrated and adopted by the largest supply-side partners in the AdTech industry. With operations spanning the US, UK, and ongoing expansion into EMEA and APAC, our system continuously interacts with up to 98% of the population in our active markets. Based in our Copenhagen office, you will join a broader Open Intelligence team of roughly 50 people, including 14+ data scientists and a strong group of engineers working across data and ML production systems. Who We Are Looking For We are looking for a Senior ML Infrast

Why project44? At project44, we believe in better. We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world. With our Decision Intelligence Platform, Movement , we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward. Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose. AI at project44 We expect every project44 team member, regardless of role or function, to actively leverage AI in their day-to-day work. Whether you're building product, serving customers, managing people, or running operations, AI is a tool you're expected to use with intent, curiosity, and judgment. We don't expect everyone to be a data scientist. We do expect everyone to be an intelligent user of AI: able to identify where it adds value, direct it effectively, evaluate outputs critically, and govern it responsibly. We invest in our team's AI fluency because we believe it's a competitive advantage for every person at project44, not just our engineers If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. Description: project44 is looking for a Staff Machine Learning Engineer to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate h

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective. You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. You Will: Model and Pipeline Automation Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models. Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models. Governance & Compliance Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards. Performance Monitoring Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. Incorporate user feedback for iterative improvements and manage necessary model retraining cycles. Cross-Functional Collaboration Act as the "glue" between Data Scientists (who build models

Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Play an active r