Learning Disabilities Jobs

Bloomreach is building the world’s premier agentic platform for personalization .We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey. We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses. We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey. We're designing the future of autonomous marketing , taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do. And we're building all of that on the intelligence of a single AI engine — Loomi — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora. Bloomreach is seeking a seasoned Staff Machine Learning Engineer to join our Search Quality team and lead the design and implementation of machine learning and Al-driven solutions that improve search relevance and discovery experiences for our customers. The Search Quality team focuses on building intelligent, scalable solutions that understand user queries, product catalogs, and behavioral signals to deliver the most relevant search results. We work at the intersection of Machine Learning, Information Retrieval, Search Relevance, and Software Engineering to solve challenging problems across the search stack. This is a Staff ML Engineer role, so we are looking for someone who can combine strong ML expertise with solid software engineering skills and take end-to-end o

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for developing the technology that helps protect our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community. You'll work side-by-side with talented product managers, data scientists, software engineers, fraud intelligence, and operations teams. Together, you'll design and build ML solutions that have direct, meaningful impact on user trust, business success, and the global Airbnb community. The Difference You Will Make: As a Senior Machine Learning Engineer on the Trust team, you will actively contribute code and ideas that shape the ML systems protecting millions of Airbnb users. You'll own and deliver ML projects end-to-end — from designing and training models to productionizing and operating them at scale, while collaborating closely with cross-functional partners. You'll tackle real-world challenges such as account takeover, fake accounts, payment fraud, and bot detection. Your work

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Early Career Learning & Development Manager At Mastercard, early-career talent is essential to building the capabilities, leadership pipeline, and workforce our business will need for the future. The Early Career Learning & Development Manager plays a critical role in shaping how new campus graduate hires—known as Launchers—transition from campus to corporate life and build the skills, confidence, networks, and business understanding needed to thrive during their first 18 months. This role helps architect and manage a cohesive, global development journey that connects orientation, in-person bootcamps, ongoing learning experiences, check-ins, manager enablement, and opportunities for applied development. Working across Learning & Development, Talent, Campus Recruiting, business leaders, managers, and HR business partners, the L&D Manager ensures that Launcher experiences are integrated, scalable, and aligned with enterprise talent priorities. The L&D Manager stays attuned to emerging priorities and strategic direction for the future of early-career development. As AI becomes increasingly integrated into how work is performed, this role will contribute insights that support strategy development and translate the evolving strategy into relevant Launcher experiences. The L&D Manager will con

Zafin is an AI platform company helping regulated institutions modernize how critical work is designed, governed, and delivered. Our technology enables organizations to move faster while maintaining the governance, accountability, and control required in highly regulated environments. Our portfolio includes Zafin AIOS , an agent orchestration platform for governed AI work; the Zafin Banking Platform , which helps banks modernize product, pricing, offers, billing, loyalty, and relationship management; and Zafin IO , an integration platform that connects data, systems, and workflows across complex enterprise environments. Headquartered in Toronto, Canada, Zafin partners with leading financial institutions across North America, Europe, the Middle East, Africa, and Asia-Pacific. As AI transforms the future of financial services, we're building the platforms that help regulated organizations adopt AI responsibly and at scale. What is the Opportunity? As a Machine Learning Engineer, part of Zafin's AIOS Product team , you will build the machine learning and AI systems that power the AIOS Knowledge Fabric and help agents reason over enterprise knowledge with accuracy, traceability, and control. You will work on practical production systems, including retrieval, ranking, embeddings, model integration, evaluation, data pipelines, model serving, observability, and the workflows that make AI outputs reliable for regulated banking environments. This is a hands-on engineering role focused on turning ML and LLM capabilities into dependable product infrastructure. This role is critical for high-quality knowledge, strong evaluation, and reliable model behavior. You will help build the foundation that allows customers to use AI agents with confidence, accountability, and measurable business value. What Will You Do? Design, build, test, and maintain ML and AI capabilities for AIOS, with a focus on knowledge retrieval, model integration, and producti

Senior Machine Learning Developer Location: Montreal, Quebec, Toronto, or Ontario About Numa Numa is building the platform to power AI-native dealerships, rearchitecting automotive service and sales with advanced AI agents that automate customer interactions, streamline operations, and reimagine how dealerships work. Numa integrates AI into every aspect of dealership functions—from rescuing customer calls and voicemails that generate more revenue, to reducing customer resolution times that drive overall customer satisfaction (CSI), to improving dealership team productivity and accountability. Numa has raised $50 million from leading investors (Google, Threshold, Costanoa, Mitsui, and Touring Capital). The Role We’re hiring a Senior Machine Learning Developer to build and ship ML/AI systems that interact with real customers thousands of times a day. Our voice agents book service appointments, rescue missed calls, and route callers through natural conversations. You’ll work across products and platforms. You’ll ship AI features including prompts, agents, tools, and production ML models, while building the evaluations and tooling that help teams ship with confidence. You’ll also contribute to our ML platform, including model serving, LLM infrastructure, and production observability. At Numa, we believe great ML is about more than building bigger models. It’s about knowing whether a change is good enough to ship. Our evaluation-first approach makes that measurable in CI and production. What You’ll Do Build conversational AI systems for phone and SMS that understand customer needs, take action, and know when to act autonomously Develop tooling such as memory, knowledge graphs, and validated customization that help agents reason and adapt to dealership needs Train, evaluate, and deploy ML models using Ray Serve and Dagster for prediction, classification, ranking, and capacity forecasting, and keep them healthy in production Create offline and online evalua

Block builds simple, powerful tools that make progress towards an economy that’s truly open to all. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone. Join us. The Role Block's Support ML Modeling team is a central driver of innovation in customer support experiences across our entire ecosystem—including Cash App, Square, and other business units. We are dedicated to advancing the state of intelligent, automated support through machine learning and generative AI. From customer-facing chatbots to smart internal tools for agents, our team builds high-impact, scalable systems that improve support quality, efficiency, and accessibility. We're building the future of support at Block: one powered by AI, voice interfaces, and smart automation. We're looking for candidates with a passion for intelligent systems, practical ML experience, and a desire to build product-driven solutions. Our ideal candidate is a leader in the field, with a proven track record of building ML systems that can accelerate our ability to scale our conversational AI initiatives. You Will Lead the end-to-end delivery of multiple ML initiatives, from planning and design through rollout, documentation, and long-term maintenance Partner strategically with risk, product, engineering, design, and operations leaders to define and drive long term ML roadmaps, informed by domain expertise and industry trends Guide the team’s direction, identifying new ML/AI opportunities and advising leadership on strategic trade

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role In an AI-native environment, the product shifts fast, new workflows emerge weekly, and customers and internal teams surface needs in real time. Someone has to meet those needs at the speed they arise. That's this role. As a lead learning experience designer, you'll own a fast-paced, high-volume learning design track focused on short, targeted, just-in-time courses — typically 15–45 minutes each, built in sprints of three weeks or less, shipping roughly 15+ courses per year. You'll build focused one-off courses that plug specific gaps: a new workflow, a role-specific skill, a tool that just shipped, an AI topic that can't wait for the next curriculum cycle. These courses are standalone, purpose-built, and often shorter-lived — responding to the moment. You'll work both proactively (scanning for emerging needs) and reactively (fielding requests from across the company and from customers). The pace is fast, the iteration cycles are tight, and the environment is dy

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role As a Staff Machine Learning Engineer on Sentry’s AI/ML team, you’ll be directly responsible for developing the models and agents used to make our product smarter and more capable. This role is crucial; you will be at the forefront of integrating AI and machine learning into our core products, from issue triage and resolution to predictive analytics for application performance monitoring. Your work will help companies around the globe gain actionable insights into their software, enabling them to build better products, faster. In this role you will Build state-of-the-art agentic AI systems to triage, debug, and solve real production issues Leverage Sentry’s novel (and massive) dataset of errors, spans, and profiles Own the development of major initiatives in the AI/ML space You'll love this job if you Are driven by impact and enjoy working on high-stakes, high-visibility projects Enjoy building things. You will have the opportunity to join the AI/ML team as one of its foundational members Thrive in cross-functional teams and enjoy building features alongside developers and product teams Qualifications Minimum 4+ years of professional experience with a MS/PhD degree in computer science, machine learning, or a related field Minimum 6+ years of professional experience with Bachelor’s degree in computer science, machine learning, or a related field Demonstrated expertise building production-grade agentic systems and tools You are comfortable writing production quality code (we use Python) Expertise with deep learning frameworks (we use PyTorch) Familiarity in deploying machine learning models at scale in production

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! At Figma we believe design doesn’t end in a file or with your designer - it includes everything that goes into the product you ship: the production code that ties it all together, the systems and developer tools that make that code reliable, the context you provide to our AI agents, and the documentation that keeps everyone on the same page. The Roundtripping Area at Figma is redefining how Designers, PMs and Engineers collaborate. We are responsible for agentic workflows enabling ideation and prototyping on production codebases as well as accelerating the journey from design to code. In 2023, we launched Dev Mode, a suite of features that give developers everything they need to navigate design files and transform designs into code. In 2025, we introduced Figma’s MCP, accelerating how ideas get to production. Looking to the future, we aim to further reduce the barriers between design to code and code to design allowing ideation, prototyping and productionalising to happen seamlessly where it most makes sense. Our Roundtripping team is expanding, and we’re hiring AI Product Engineers across multiple levels in the UK. We’re looking for people who have built generative AI products and are eager to lead AI efforts end-to-end, from early ideas to production. Join us in shaping the future of AI at Figma. What you’ll do at Figma: Build and evolve Dev Mode our MCP tools and Make, Figma’s leading tools for dev/design collaboration Take part in building new 0→1 products within the agentic coding space Col

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them. The Surfaces Podcasts team owns podcast recommendations across some of Spotify’s most visible surfaces, including Home and the Now Playing view. We build and improve the recommendation systems that help listeners discover their next favorite show or episode while helping creators reach the right audiences. As a Staff Machine Learning Engineer, you’ll help shape the future of personalized discovery and engagement at Spotify. You’ll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences for listeners at global scale. You’ll take models from research to production, help set technical direction in ambiguous problem spaces, and solve complex personalization challenges across Spotify. What You'll Do Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience. Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally. Build content recommendation systems for emerging agentic and AI-powered user experiences. Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches. Partner closely with Product Managers, Engineers, Data Scientists, and Designers to define and execute experimentation strategies. Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency.

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. ABOUT THE TEAM + ROLE We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The AI Platform & Agentic Apps team builds the agent platform behind every AI agent at Robinhood. Today it gives a growing number of engineers and employees an AI teammate that ships code, queries data, and runs operational workflows on their behalf. We're building toward the same platform powering the agents millions of customers interact with directly, in real time. These agents don't just answer questions — they're designed to take real action across carefully curated meta harnesses. This is agentic AI at real scale, in a regulated financial environment, and it will change how Robinhood works! As a Staff Machine Learning Engineer on the AI Platform & Agentic Apps team, you will design and build the harness that every agent at Robinhood runs on. A critical part of the role is making those agents trustworthy at scale: trajectory-level evals that measure how an agent reasons and acts, and action guardrails — permission models, approval gates, and sandboxing — built as platform primitives that other teams adopt. You'll be a technical anchor on a growing, high-caliber team, collaborating with product, infrastructure, and fellow ML engineers to take ambitious ideas from

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Global Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. We're looking for a Machine Learning Engineer to join our London office as part of a Global DoorDash Engineering team (working hybrid, 3 days in the office). Our New Verticals team exists to grow monthly active usage outside of restaurant ordering — groceries, retail, and everything in between. That means turning someone who only orders restaurant food into someone who also uses the app for a grocery run, and turning dormant users into active ones. You'll work on the surfaces that make that happen: the homepage, vertical landing pages, and the notifications that bring people back. This role sits closer to the personalisation and ranking side of that mission, working alongside colleagues across DoorDash, Deliveroo and Wolt. What You'll Be Doing Build and improve ranking models for vertical landing pages (grocery, retail), deciding what a user sees first when they land on a store page Design models that blend new-vertical content into a homepage built around restaurant ordering, without disrupting the core experience Build personalisation models that translate a user's existing behaviour into relevant recommendations for verticals they haven't tried yet Contribute to notification targeting — who gets notified, with what message, and when, to drive adoption of new verticals What You'll Need to Thrive Minimum 3+ years of experience as an ML Engineer or Data S

Join Adobe Security Engineering and help build the ML and generative AI capabilities that protect Adobe, our products, and our customers. Our team sits where cybersecurity, large-scale data, and AI meet, building models for anomaly detection, threat detection, investigation, and security analytics across some of Adobe's largest datasets. As a Staff Machine Learning Engineer, you'll design, build, and scale production ML systems spanning deep learning, behavioral modeling, embeddings, and agentic AI. You'll write code, train models, run experiments, and help shape the architecture the broader team builds on. You'll also partner closely with data, platform, and security engineers across Adobe. The Challenge Architect end-to-end ML systems for high-volume security data, turning experiments into reusable capabilities. Own the ML lifecycle, from feature engineering through training, deployment, monitoring, and retraining. Build LLM and agentic AI capabilities for security investigation, including retrieval-augmented generation. Design evaluation frameworks that measure model quality and help analysts trust and validate results. Work with data and platform engineers to scale pipelines and resolve system bottlenecks together. Mentor engineers and help guide technical direction through design reviews and hands-on collaboration. What you bring Experience running production ML systems from early experimentation through sustained operation at scale. A strong background training models with PyTorch and transformers, including behavioral modeling and anomaly detection. Comfort with distributed compute like Spark, cloud platforms like AWS, and MLOps tools like MLflow. Experience building with LLMs or generative AI, along with evaluating how they behave in production. Strong Python and SQL skills, and solid software engineering habit

We’re looking for a Senior Digital Learning Experience Designer to join our Learning & Inclusion team, the group responsible for creating learning experiences that help every Spotify band member grow, belong, and do their best work. You’ll bring together instructional design, visual design, storytelling, and broader learning and development expertise to create inclusive and effective experiences at scale. You’ll partner with subject-matter experts, people leaders, and Learning & Inclusion colleagues on company-wide initiatives, from leadership development to programs that bring Spotify’s values to life. What You'll Do Lead the end-to-end design of learning experiences, from needs analysis and curriculum architecture through development, launch, and evaluation. Partner with subject-matter experts and stakeholders to identify performance needs and turn them into clear learning objectives and practical solutions. Design learning journeys across live, digital, blended, and self-directed formats using evidence-based learning principles. Create engaging learning materials, including eLearning, facilitator guides, participant resources, job aids, presentations, and micro-learning experiences. Use visual design and storytelling to make complex ideas clear, memorable, and engaging while creating experiences that feel unmistakably Spotify. Build interactive digital learning experiences using AI-assisted workflows and authoring tools such as Articulate Storyline or Rise, Adobe Captivate, or similar platforms. <li data-section-id="widzc4" data-start="1865" data-end=

We’re looking for a Senior Digital Learning Experience Designer to join our Learning & Inclusion team, the group responsible for creating learning experiences that help every Spotify band member grow, belong, and do their best work. You’ll bring together instructional design, visual design, storytelling, and broader learning and development expertise to create inclusive and effective experiences at scale. You’ll partner with subject-matter experts, people leaders, and Learning & Inclusion colleagues on company-wide initiatives, from leadership development to programs that bring Spotify’s values to life. What You'll Do Lead the end-to-end design of learning experiences, from needs analysis and curriculum architecture through development, launch, and evaluation. Partner with subject-matter experts and stakeholders to identify performance needs and turn them into clear learning objectives and practical solutions. Design learning journeys across live, digital, blended, and self-directed formats using evidence-based learning principles. Create engaging learning materials, including eLearning, facilitator guides, participant resources, job aids, presentations, and micro-learning experiences. Use visual design and storytelling to make complex ideas clear, memorable, and engaging while creating experiences that feel unmistakably Spotify. Build interactive digital learning experiences using AI-assisted workflows and authoring tools such as Articulate Storyline or Rise, Adobe Captivate, or similar platforms. <li data-section-id="widzc4" data-start="2096" data-end