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About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This internship is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments. Preferred Qualifications: Currently pursuing a PhD in computer science, machine learning, or a related field. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas. Experience developing and evaluating large-scale models or machine learning systems. Familiari

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Our team is a fast-growing group of committed researchers and engineers. The mission of the team is to build reliable machine learning systems and optimize audio inference serving efficiency using innovative techniques. As an engineer on this team, you will work on advancing core audio model serving metrics, including latency, throughput, and quality by diving deep into our systems, identifying bottlenecks, and delivering creative solutions for audio processing and streaming workloads. You’ll collaborate closely with both the training and serving infrastructure teams to ensure seamless integration between model development and deployment, with a special focus on real-time and streaming audio inference. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. You may

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Large Language Models (LLMs) continue to push the boundaries of what AI systems can do — but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including: model architecture and MoE routing optimization decoding and inference-time algorithm improvements software/hardware co-design for GPU acceleration performance optimization without compromising model quality Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. As a Staff Research Engineer, you will develop, prototype, and deploy techniques that materially improve how fast and efficiently our models run in production. You may be a good fit

Datadog is entering a new chapter in how our product looks, feels and operates. We're building a small, high-leverage Design Lab team to define that evolution, and we're looking for a Senior Staff Visual Designer to author it. Our design system powers everything we ship. Now we're ready to evolve it. As Datadog expands into AI-driven experiences and more complex product surfaces, the visual language needs to grow with it. This is the role that decides what that language is — someone with taste, judgment, and the confidence to set a direction and defend it. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Define and evolve Datadog’s visual language across product surfaces. Lead exploratory and concept work, creating a range of distinct visual directions for the next generation of the product. Synthesize product context, research, references, and stakeholder input into clear visual principles and a coherent point of view. Establish the quality bar for typography, color, composition, iconography, imagery, motion, and visual expression across the platform. Create high-fidelity product exemplars and prototypes that make an emerging direction tangible. Partner deeply with Brand, Product Design, Motion, and Design Systems to test and refine the direction across different surfaces. Influence executives and senior stakeholders through clear, persuasive visual storytelling. Guide and critique the work of other designers, helping the visual direction remain coherent as it evolves. Help shape how visual exploration, critique, and craft are integrated into Datadog’s design process. You will report directly to the Design Director and work as part of a small, focused team defining the future state before it scales across hundreds of designers and engineers. Who Yo

The product operations team enables product excellence at scale at Datadog. With over thirty standalone products on a single platform, product operations drives consistency, efficiency, and quality across the organization. As a Product Operations Manager, you will help the product organization do its best work. You'll build and scale the processes, frameworks, and cross-functional workflows that enable PMs and their partners to ship effectively. This includes touchpoints with inbound, delivery, outbound workstreams in product development. This is a role for someone who thrives in the space between teams: driving alignment, removing friction, and ensuring that the operational foundations of the product org can keep pace with Datadog's growth. At Datadog, we place value in our office culture, the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Own and improve the full Product Development Life Cycle . Own and drive operational excellence for product launches. This includes coordinating across Product, Engineering, Marketing, Sales, Customer Success, and Support to ensure we are ready to bring quality products and support to our customers. Build AI-powered workflows and agents that automate and accelerate operational work. From customer feedback triage to launch tracking to cross-functional reporting, you'll experiment with and deploy AI tools and custom agents to help the product org move faster and smarter. Build and maintain a single source of truth for launches giving cross-functional partners real-time visibility into what's shipping, when, and what's needed from each team. Drive centralized product knowledge and enablement , ensuring PMs and stakeholders have the tools, resources, templates, and context they need to succeed and making it easily discoverable. Analyze and quantify product signals. Query pro

As the Senior Product Manager for the Actions & Automations team, you will own the ecosystem that enables customers, partners, and Datadog teams to build, deploy, and operate AI agents on Datadog. You will drive the strategy and execution for the platform capabilities, developer experience, integrations, and extensibility model that make Datadog the best place to build agents that understand and act on production systems. Modern engineering organizations are entering a new era where software is not only monitored and operated by humans, but increasingly by AI-powered agents. As agentic workflows reshape how teams build, operate, secure, and troubleshoot systems, customers need a platform for creating specialized agents, connecting them to business and engineering systems, governing their behavior, and extending them to solve unique organizational problems. You will define and build the ecosystem that makes this possible. Agent Builder sits at the intersection of Datadog's products, AI capabilities, and ecosystem strategy. You will have the opportunity to work across the breadth of the Datadog platform, partner with teams throughout the company, and help establish Datadog as the foundation for operational AI. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Define the vision, strategy, and roadmap for Datadog's Agent Builder platform and ecosystem. Own the core platform capabilities that enable customers and partners to create, customize, deploy, and manage AI agents. Drive the extensibility model for agents, including integrations, tools, actions, context sources, APIs, SDKs, and developer workflows. Shape how agents perform actions across Datadog products and third-party systems. Partner closely with AI, platform, infrastructure, and product tea

Role Overview We’re looking for a Senior Product Designer with a passion for building platform features that impact UX at a massive scale. As a member of AAA, you’ll work across a breadth of problem spaces on deeply technical topics, such as governance, access, teams, identity, and multi-org UX. You’ll lead design for features that mediate how Datadog’s biggest customers use the platform and manage what their employees can see and do. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do AAA is a highly technical product environment, where designers strive to understand the technical workflows, constraints and opportunities within this domain. As you develop subject matter expertise, you’ll use your influence as a Senior designer to drive the roadmap and vision. Day-to-day, you’ll work closely with your PM and engineering partners to understand customers’ pain points, explore solutions, and build UI that ships. Prototyping in code creates the opportunity to share high-fidelity ideas at early stages, even if the design itself is low-fidelity. Tight feedback loops let your team iterate quickly, building towards an ideal vision for the best possible experience while you ship incremental steps towards that goal. In addition to making the work, you will also share your work with stakeholders at varying levels of seniority, all the way up to executive leadership level. Your crisp context setting and clear description of your solution will help people understand your choices and sell them on your proposal. Your work will up-level the quality bar for what an admin experience can look like. While you’ll leverage Datadog’s design system where it makes sense, you won’t let it prevent broad exploration of different design patterns in the service of finding the optimal solu

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role You'll own the quality bar for Notion AI products. You’ll work with product and engineering teams to build systems to define what “good” looks like, measure our progress, and drive changes to deliver reliable and high-quality AI experiences. Your work directly shapes how Notion's AI products behave for millions of users. This isn't a traditional software engineering role. It’s an art & science role . You won't spend your days writing code. Instead, you'll focus on understanding and shaping how our AI products behave through context engineering, designing evaluation systems, and analyzing data. This team sits in our AI engineering team, working directly with engineering, product, design, and data. This role is a unique blend of ops, strategy, and product thinking. Day to day, you'll live in production data, ship prompt fixes, run evals and, in effect, shape our quality strategy. As part of that you'll shape Notion's model strategy and work directly with frontier AI labs (OpenAI, Anthropic, Google) to evaluate and launch new models. We're looking for problem-seeking generalists interested in 0 → 1 : curious people wi

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. About Fern, a Postman Company Fern helps software companies build a world-class API experience. Our customers include industry leaders like Nvidia, Square, and Twilio, as well as fast-growing AI companies like ElevenLabs and OpenRouter. In the next year, the majority of API integrations will be implemented by AI agents. Agents don’t read marketing pages. They need strongly typed schemas, structured endpoints, deterministic contracts, and documentation that can be fed into a context window. Our team is small and talent-dense. We’re a team of builders from Google, Palantir, Amazon, and Uber, working together in New York City. About the Role As a Senior Software Engineer at Fern, you’ll build APIs, scale AI infrastructure, and design developer experiences that reach millions of people. Scale infrastructure to keep up with growth: Work on AI systems deployed on Vercel, AWS, and Turbopuffer that must be performant, reliable, and secure under real-world load. Stay close to customers: We work directly with API teams at companies like Nvidia, Twilio, and Square. You’ll debug real production edge cases, shape APIs ba

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. About Fern, a Postman Company Fern helps software companies build a world-class API experience. Our customers include industry leaders like Nvidia, Square, and Twilio, as well as fast-growing AI companies like ElevenLabs and OpenRouter. In the next year, the majority of API integrations will be implemented by AI agents. Agents don’t read marketing pages. They need strongly typed schemas, structured endpoints, deterministic contracts, and documentation that can be fed into a context window. Our team is small and talent-dense. We’re a team of builders from Google, Palantir, Amazon, and Uber, working together in New York City. About the Role As a Staff Software Engineer at Fern, you’ll build APIs, scale AI infrastructure, and design developer experiences that reach millions of people. Set technical direction: Drive system design decisions around data modeling, performance, correctness, and reliability. Identify scaling bottlenecks before they become problems. Build for durability and scale: Ensure our systems are performant, observable, secure, and resilient under real-world production load across infrastructur

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a Senior Solution Engineer who is accustomed to solving customer’s most complex problems and closing large deals. In this role you will work directly with the sales team and channel partners to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. As a Snowflake Solution Engineer you must share our passion about reinventing the database space, thrive in a dynamic environment and have the flexibility and willingness to jump in and get things done. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with technical audiences. In This Role You Will Get To Present Snowflake technology and vision to executives and technical contributors at prospects and customers Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in relation to them. Collabor