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About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role As an Applied Scientist at Dialpad, you'll be an integral part of our AI team, conducting R&D to power the next generation of autonomous voice agents and delivering features for transcribed voice and chat message data in the business communications domain. We have several research themes, including developing multi

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. This is a hybrid role. It requires going to the local office 3 times a week. The Auth0Lab Team We are a small team of engineers exploring new Auth0 products and features ideas. We take things from 0 to 1 and we look to shape the future of identity. Our team has had a big role shaping the identity industry: we were all early at Auth0, which shaped how devs do authentication as part of Auth0Lab we incubated Auth0 FGA which redefined how authorization is done across the industry and we also incubated Auth0 for AI agents which defined auth for AI agents We are currently focused on enabling builders and companies of any size to ship production grade AI agents, by helping them with identity and security. We believe data, and developing our own models will play a huge role in this. The role We are looking for a Principal Applied AI Scientist to take product ideas from 0 to 1 and define how we do new AI product innovation. You'll have a lot of independence: you set the technical direction for AI, and experiment fast with minimal process. With that comes real ownership: you'll be the first AI/ML person in the team, so you'll often be figuring it out without a research org behind you. This is a hands-on role. Publishing papers and open sourcing results might happen as it helps us and the industry, but is not our main goal. We have a lot to teach you about security, auth, developer products and many other things. And we also want to learn from you. Join us to ha

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

Who We Are At Justworks, you’ll enjoy a welcoming and casual environment, great benefits, wellness program offerings, company retreats, and the ability to interact with and learn from leaders in the startup community. We work hard and care about our most prized asset - our people. We’re helping businesses get off the ground by enabling them to focus on running their business. We solve HR issues. We’re data-driven and never stop iterating. If you’d like to work in a supportive, entrepreneurial environment, are interested in building something meaningful and having fun while doing it, we’d love to hear from you. We're united by shared goals and shared motivations at Justworks. These are best summed up in our company values, which are reflected in our product and in our team. Our Values If this sounds like you, you’ll fit right in. Who You Are You are self-driven and like to work with others to remove roadblocks. You are curious and love to explore and learn new technologies. You have demonstrated the ability to build, deploy, and maintain large-scale, complex applications. You care more about solutions and impacting the customer experience than using a particular tool or framework. About the role: You will join a small, highly autonomous cross-functional team to build AI agents that fundamentally transform how operations work at scale. Instead of writing bespoke software for every workflow, we are developing an agent platform that can read operational knowledge, reason about it in context, and execute tasks end-to-end. This approach allows us to scale complexity through knowledge and reasoning, rather than simply through code. This is an opportunity to join a foundational team, which currently consists of fewer than five engineers. The work spans critical areas including LLM-powered agent design, robust backend service architecture, tool and integration development, and sophisticated knowledge infrastructure. We are seeking a Senior Software Engineer with a strong pas

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 . The Pinterest Labs group is dedicated to the development and research of applied machine learning. Our initiatives span a diverse range of AI/ML fields, including fundamental computer vision, multimodal large language models, multimodal representation learning, generative modeling, heterogeneous graph neural networks, and recommender systems. By building foundation ML models that utilize our extensive knowledge graph and billions of Pins, we aim to significantly enhan

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. Lyft is looking for software engineers from a scope of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empowers us to iterate quickly, while focusing on delighting our passengers and drivers. The Applied AI team is looking for a senior software Engineer to join the Recommendations team. You will build the backend systems that decide what we surface to riders. You will architect the pipelines and services that turn rider context and signals into the right offer at the right moment, driving a measurable impact on rider experience. Responsibilities: Establish engineering best practices and patterns; help uplift the team's craft and drive a culture of engineering excellence Drive high-impact projects and innovate new solutions to deliver the best user experience Produce and drive scalable system design for large, complex features — from idea through execution and launch Mentor engineers on the team, providing technical guidance and supporting their growth Champion and evangelize the use of AI tools to accelerate engineering productivity across the team, sharing patterns and best practices that raise the bar for how the team builds Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and share knowledge across the team Participate in the team's on-call rotation; identify, triage, debug, and resolve issues across our applications and platforms Excellent communication skills and the ability to explain the various trade offs made in decisions Manage project priorities, deadlines, and deliverables. Experience: BS/MS or

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. Lyft is looking for software engineers from a scope of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. The Applied AI team is looking for a Backend Engineer to join the AI Entries team. You will build the foundational infrastructure that connects Lyft to emerging AI ecosystems and devices and architect the APIs and orchestration layers that allow third-party agents and multimodal interfaces to interact with Lyft. By building these robust integration, you will help make Lyft available where our riders are. Responsibilities: Establish engineering best practices and patterns; help uplift the team's craft and drive a culture of engineering excellence Drive high-impact projects and innovate new solutions to deliver the best user experience Produce and drive scalable system design for large, complex features — from idea through execution and launch Mentor engineers on the team, providing technical guidance and supporting their growth Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and share knowledge across the team Participate in the team's on-call rotation; identify, triage, debug, and resolve issues across our applications and platforms Have the ability to explain the various trade offs made in decisions Manage project priorities, deadlines, and deliverables. Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or related field or equivalent practical experience. 5+ years of software engineering/production

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 a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

About the Team The DoorDash Research Fellowship is a 3-month program (extendable to 6 months) looking for Summer and Fall 2026 cohorts, for researchers and engineers who want to work on the hardest applied ML and AI problems in local commerce. Fellows are given the resources, autonomy, and access to real-world operational data needed to pursue ambitious research directions — with the goal of producing work that influences both the field and how DoorDash operates at scale. This program is modeled on the best external research fellowships: fellows are treated as independent researchers, not as junior employees on a product team. You pick the problem (within a set of priority areas), you own the direction, and you publish or ship the outcome. You’re excited about this opportunity because you will receive… Dedicated compute allocation sized to the research agenda — GPU clusters for training and inference budgets for experimentation Full access to DoorDash's research infrastructure — our internal RL stack, training and evaluation pipelines, RL environments built on real operational systems, agent evaluation harnesses, and the tooling our own research teams use day-to-day. Fellows are first-class users, not sandboxed visitors. Access to DoorDash operational data — real-world datasets spanning logistics, merchant operations, consumer behavior, and marketplace dynamics, under appropriate data governance Research mentorship from senior researchers and engineering leaders at DoorDash, plus a named research sponsor for each fellow who meets with you weekly and is accountable for unblocking your work Speaker series featuring leading researchers and practitioners from academia and industry — faculty from top ML programs, research leads from frontier AI labs, and senior operators from across tech. Fellows get dedicated 1:1 time with speakers when possible. A cohort of fellows working alongside you — a small, tight-knit group of researchers tackling different problems but sharing

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a Masters degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have work

About the Team The Sales Compliance team is responsible for ensuring revenue assurance and designing effective OTC compliance and controls across DoorDash’s and Deliveroo’s Merchant organization. The Sales compliance team is part of the larger Sales Strategy & Operations team, which accelerates productivity and develops go-to-market strategies and processes to support our sales organization. This group builds the engine and foundation for DoorDash to achieve the best selection for our platform and grow revenues across all business lines. About the Role We are seeking a Manager, Sales Compliance to build the vision and roadmap for DoorDash and Deliveroo’s Merchant revenue assurance program. This role will oversee our key revenue related SOX controls, which ensures all commission rate changes and merchant pricing terms are contractually supported, accurately configured in system, and correctly applied to charges. This role is responsible for overseeing monthly contract-to-system-to-charge reconciliations, investigating exceptions and partnering cross-functionally with product, engineering, accounting, legal and audit teams to remediate underlying root cause issues that help accelerate DoorDash and Deliveroo’s revenue growth. They will also demonstrate operating effectiveness for all order-to-cash controls to Accounting, Internal and External Audit. This role will support all of DoorDash’s and Deliveroo’s marketplace products, business lines and countries/geos. You will report to the Senior Manager, Sales Compliance. This role is hybrid, based in Vancouver, Canada. You’re excited about this opportunity because you will… Own the end-to-end effectiveness of key SOX revenue controls, holding the program to the standard of 100% of merchants charged correctly, 100% of the time Be accountable for the effectiveness of contract → system → delivery-level charge reconciliations, reviewing and challenging outputs to ensure accuracy, identify trends and assess risk areas

Head of Talent Acquisition Location: New York, NY, onsite 5 days per week Role type: Full time Reports to: President The Role Flowcode builds the infrastructure that turns real world touchpoints into measurable, actionable first party IDs, enabling F500 brands to personalize consumer experiences at scale. One of Flowcode’s founding principles is “the product is the team, and the team is the product.” We treat hiring with the same level of rigor we apply to product development. We have an extremely high hiring bar (the “pinhole process”), which to date we have applied by brute force. Our CEO, President and our executive team each personally read resumes, sit on interview loops, and close candidates. It works. But it also means our hiring speed is capped by the calendars of the ten busiest people in the company, and our pipeline stops the moment one promising candidate appears. We are not hiring a coordinator, a req-filler, or a "people partner who also does recruiting." We are hiring the person who owns the talent bar, the pipeline and the close. You are relentless in your proactive pursuit of top 1% talent, and you never consider the pipeline “good enough”. You treat every day as an opportunity to source the next generation of leaders for Flowcode, and you are consistently refining differentiated strategies to attract and retain elite talent. What you'll own The talent bar: You define, in writing, what "top 1%" means for each function at Flowcode, with calibrated scorecards and interview questions — and you hold the line when a hiring manager, or anyone else at the company, including the executive team, wants an exception. An always-on pipeline: You do not just open requisitions when a seat empties. You have named, warm, mapped talent for our most critical roles at all times, including seats that are currently filled. Outbound and referral as the default: Job boards produce volume; direct sourcing and referrals produce our best people. You flip the

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