Learning Disabilities Jobs

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

About Bazaarvoice At Bazaarvoice, we create smart shopping experiences. Through our expansive global network, product-passionate community & enterprise technology, we connect thousands of brands and retailers with billions of consumers. Our solutions enable brands to connect with consumers and collect valuable user-generated content, at an unprecedented scale. This content achieves global reach by leveraging our extensive and ever-expanding retail, social & search syndication network. And we make it easy for brands & retailers to gain valuable business insights from real-time consumer feedback with intuitive tools and dashboards. The result is smarter shopping: loyal customers, increased sales, and improved products. The problem we are trying to solve : Brands and retailers struggle to make real connections with consumers. It's a challenge to deliver trustworthy and inspiring content in the moments that matter most during the discovery and purchase cycle. The result? Time and money spent on content that doesn't attract new consumers, convert them, or earn their long-term loyalty. Our brand promise : closing the gap between brands and consumers. Founded in 2005, Bazaarvoice is headquartered in Austin, Texas with offices in North America, Europe, Asia and Australia. It’s official: Bazaarvoice is a Great Place to Work in the US , Australia, India, Lithuania, France, Germany and the UK! The Role: We are seeking a highly experienced and strategic Staff Machine Learning Engineer to join our AI & Data Science team. This is a senior-most individual contributor role where you will be responsible for owning the end-to-end Machine Learning Development Lifecycle (MDLC). You will architect, build, and deploy production-grade, scalable ML systems that transform massive volumes of user-generated content into actionable insights for our customers. This position requires a proven track record of solving complex, unstructured data challenges and a deep expertise in buildi

JOB RESPONSIBILITIES: A highly collaborative, fast-growing team at Internal Alpha Capture (IAC), Point72 is developing AI-driven equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, proprietary data sources, and unparalleled computing power. We are looking for exceptional machine learning researchers to join our efforts. Researchers will work closely with our experienced team members and apply the full breadth of their machine learning knowledge to unique, proprietary datasets, and develop novel trading signals that have high impact. Prior experience in the financial industry is not required. Key responsibilities may include: Managing all aspects of the research process, including ideation, method selection, implementation, evaluation, and eventual application. Identifying, adapting, and extending existing models in the broad field of machine learning; conducting novel research as needed, to develop new signals that can enhance portfolio returns, or predict other variables of interests. Staying up to date on the advances in AI/ML and related technological innovations to provide recommendations on new models and tools and identify emerging opportunities. DESIRABLE CANDIDATES: Master’s or PhD in machine learning, computer science, statistics, or related fields. Knowledge and experience in any of the following areas are strongly preferred: modern sequence models, graph neutral nets, reinforcement learning, LLMs. Prior research experience utilizing machine learning over large, possibly noisy, data sets. Strong analytical and quantitative skills, and a detail-oriented mindset. Strong proficiency in machine learning libraries such as Torch, JAX or TensorFlow. Competence in Python, cluster environment, and general software engineering principles (source control, testing, collaborative workflow). Excellent written and verbal communication skills, willing to proactively engage other team members in helping to foster a highly coll

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! Figma is seeking a versatile and experienced Machine Learning / AI Engineer to join our growing AI team, working at the intersection of applied machine learning, infrastructure, and product innovation. Whether you’re building intelligent search systems, crafting scalable data pipelines, or enhancing AI-powered creativity tools, your work will drive user productivity, shape new product experiences, and advance the state of AI at Figma. You’ll collaborate closely with engineers, researchers, designers, and product managers across multiple teams to deliver high-quality ML-driven features and infrastructure. This is a high-impact, cross-functional role where you’ll shape both foundational systems and user-facing capabilities. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: Design, build, and productionize ML models for Search, Discovery, Ranking, Retrieval-Augmented Generation (RAG), and generative AI features. Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows. Collaborate with AI researchers to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance. Work with product engineers to define and deliver impactful AI features across Figma’s platform. Partner with infrastructure engineers to develop and optimize systems for training, inference, monitoring, and deployment. Explo

About Appier Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. About the Role We are looking for a Machine Learning Scientist (LLM & Agents) to join the Enterprise Solution Science Team. This team focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data. In this role, you will own agent features end to end — from problem definition and design, to shipping, to measuring and improving quality in production. What You’ll Work On You will contribute to the design, development, and productionization of one or more enterprise AI agents, including: Marketing Agent: Empower marketers to improve conversion rates and drive revenue growth. Strategy Agent: Transform raw data into actionable, revenue-driving strategies and high-potential audience segments. Data Analysis Agent: Answer business questions by planning multi-step analyses and running SQL over large customer datasets, with every number traceable to the query that produced it. Sales and Service Agent: Drive sales conversion, increase average order value (AOV), and deepen brand engagement and customer loyalty through real-time, 24/7 AI-powered support. Build agent capabilities as reusable skills and MCP tools, and design tool interfaces that agents use correctly and efficiently Bring predictive models (e.g. propensity, churn, recommendation) into agent workflows and next-best-action suggestions Build evaluation — test sets, LLM-as-a-judge, production trace review — and use it to decide what ships Make agents faster and cheaper without losing answer quality, through c

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Within Pinterest, the Pinterest Labs organization focuses on applied ML research and development. Labs focuses on a broad variety of AI/ML initiatives, such as core computer vision, multimodal representation learning, heterogeneous graph neural networks, generative modeling, recommender systems, etc. This is the group that develops foundation ML models that fully leverage the tens of billions of Pins and the associated knowledge graph to improve the core product. We are currently hiring for the visual modeling team in Labs, which focuses on developing Pinterest Canvas. Canvas is a foundation text-to-image model developed internally for helping various visualization, inpainting, and outpainting products. In this role, you’ll get to work with Pinterest’s rich visual-text dataset to build large-scale generative models which are continuously being s

About Appier Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. The Impact You’ll Make at Appier Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team , which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery. In this role, you’ll directly impact the efficiency and profitability of ads campaigns by improving models for bidding, pricing , and personalized content recommendation , while ensuring system robustness and scalability in a dynamic market environment. What You’ll Work On Design, implement, and productionize state-of-the-art ML models to improve campaign outcomes. Analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization. Collaborate cross-functionally with engineering, product, and data teams to identify opportunities, define roadmaps, and deliver impactful solutions. Continuously improve system performance through offline experimentation and online testing (e.g., A/B tests, incremental learning). What We’re Looking For Bachelor’s degree in Computer Science, Mathematics, EE, or related field; Master’s or PhD preferred. 4+ years of industry experience in ad tech , with a focus on performance optimization. Proven experience in applied machine learning , especial

P-1408 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products . Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2025, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 10+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks,

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

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? Identify areas w

Our Perception team is responsible for using our sensor data to understand the complex and dynamic environments where we drive. In this role, you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms. We are creating new algorithms for segmentation, tracking, classification, and high-level scene understanding, and you could work on any (or all!) of these components. As a Senior Staff ML Engineer, you will lead the development of machine learning algorithms that can range in influence from onboard autonomy to offboard autonomy and validation. You will collaborate closely with other teams specializing in Prediction, Planning, Simulation, and Safety Validation, influencing our overall technical stack. Your role will look at problems in a way that crosses team boundaries to prototype new approaches that influence the long term technical direction of multiple organizations within the company. The impact of the role can be in the form of impacting immediate company milestones to leading forward-looking exploratory projects. Responsibilities Develop new algorithms to understand the scene around the robot, and how that scene would evolve through time Build multi-modal foundation models for on-vehicle and offline applications Develop new algorithms to apply generative AI to simulation to improve the realism of our offline validation systems Leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field Provide technical mentorship to the broader group of ML developers at Zoox Collaborate with engineers on Prediction, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying Deep Learning models on sensor data-Experience

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t

About Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Role/Responsibilities: We are seeking a quantitative researcher for the Cubist Machine Learning Research group with experience in machine learning, especially recent deep learning and natural language processing technology. Researchers will use a rigorous scientific method to develop sophisticated trading models and shape our insights into how the markets will behave. Successful researchers manage all aspects of the research process including data ingestion and processing, data analysis, methodology selection, implementation and testing, prototyping, and performance evaluation. Researchers will be introduced to industry standard datasets, including understanding which data may be relevant to a certain model or financial problem; how to collect, parse, and clean the data; how to incorporate the data into innovative functional models; how to construct and develop features from raw data; and how to estimate effectiveness of such features. Researchers will also be provided with the opportunity to implement the full breadth of their knowledge and training to actively participate in all stages of research & development of financial models through use of machine learning. Based on experience from working with existing industry-standard models and algorithms, researchers will learn how to construct their own models in order to solve complex financial problems and enhance data prediction capabilities within the financial services industry. Requirements: PhD or PhD candidate in machine learning, computer science, statistics, or a related field Experience with sequential modeling and time

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the role In this role, you will collaborate closely with researchers and engineers on the Learned Behavior teams to tackle plan generation challenges in autonomous driving. You’ll apply state-of-the-art generative modeling techniques—ranging from cutting-edge diffusion, flow matching, energy-based models, and SoTA algorithms—in order to develop novel solutions that generate safe, comfortable, and efficient driving behaviors in the most challenging real world situations. Beyond core research, you’ll own the end-to-end lifecycle of your models, productizing them for robust, real-world autonomous driving deployments on a global scale. About the Work Develop and scale state-of-the-art generative models—especially diffusion architectures, flow-matching techniques, and energy-based models —for autonomous plan generation. Build generative models with foundation models. Leverage large language models and world foundation models for r