About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role You'll build the platform that powers Hark's AI agent — the runtime, the infrastructure, the primitives. Everything that makes the intelligence actually works in production. That means owning the hard systems problems, such as low-latency streaming, reliable tool execution, memory and context at scale, and orchestration logic that holds up under real usage. You will be building the foundation that everything else runs on. This is a high-ownership role on a small team. You'll work directly with the people building the models and the people shipping the product, and the systems you build will define what's possible for both. Responsibilities Build the core runtime that powers Hark's agent platform. Orchestration, tool execution, memory retrieval, streaming, and the systems that make all of it work reliably together. Own features end-to-end, from early prototyping alongside model researchers to production deployment and iteration based on real usage. Architect the platform primitives that the rest of the product team builds on. Agent runtimes, execution sandboxes, memory APIs, streaming pipelines. Instrument and evaluate the product. Write evals, track quality regressions, and feed signals back into the model and product loop. Work across th
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ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE This role sits at the frontier of our research agenda. You will pursue open problems at the intersection of post-training methodology and performant inference, and then collaborate with research engineering to translate findings into production systems. A meaningful portion of your time will be dedicated to research that deepens our understanding of how models learn, alignment, and architectural efficiency — questions that may not have immediate product application. The remainder will be directed toward research that solves concrete problems for Baseten's platform and customers, who are the fastest growing AI companies in the world like Cursor, Lovable, and Notion. We are looking for someone with sharp research taste and genuine creative instinct for problem selection. Someone who can identify questions that matter, design clean experiments to answer them, and push the state of the art. The environment here is not theoretical, but rather research that can be validated with eager customers who are serving billions of tokens a second. The Manifesto: https://labs.baseten.co/manifesto RECENT RESEARCH Towards infinite context windows: neural KV cache compaction Dense, on-policy or both? Repeated kv cache for long-running agents Distillation without the dark – replicating black-box on-policy distillation on Baseten RESPONSIBILITIES Define and pursue a research agenda spanning both foundational and applied work, with t
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. About the role We're hiring a Software Engineer to work on Bugbot . Bugbot reviews pull requests, catches bugs, suggests improvements, and is becoming a critical part of how engineering teams ship software. As LLMs rapidly mature, the surface area of what Bugbot can do is expanding just as fast. From the model integration and agent harness improvement to the product UI, integrations, and onboarding experience, you’ll maintain Bugbot being the industry's best AI code reviewer. This is a full-stack IC role where you'll ship features end-to-end and directly shape how millions of engineers interact with AI during code review. What you’ll do Launch new Bugbot features end-to-end from defining the feature and building the UI to wiring up the backend and iterating on model behavior so that each release meaningfully improves code review quality. You can check out Bugbot blog post for some examples of how Bugbot was improved in the past: https://cursor.com/blog/building-bugbot . Evolve the review pipeline adapting prompting strategies, model routing, context selection, and agent orchestration to take advantage of new capabilities while managing cost and latency. Build integrations that e
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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lake using open formats like Apache Iceberg, delivering deep correlation and long-term analytics at dramatically lower cost. A dynamic Knowledge Graph and chat-based AI SRE provide rich context and guided workflows so teams can move from detection to root cause and resolution significantly faster. The Infrastructure team at Observe by Snowflake is responsible for building, scaling, and operating the development and production environments that power our observability platform. We are a small, highly collaborative team with a broad scope, focused on delivering reliable infrastructure while continuously improving the systems that support our engineers and customers. What You’ll Do Design, build, and operate scalable cloud infrastructure in AWS supporting a high-scale observability platform. Improve system reliability, performance, and operational visibility across development and production environments. Develop and maintain CI/CD pipelines and internal tooling to improve developer productivity and deployment safety. Identify and mitigate security risks, and help maintain intern
About Prodigal Prodigal is the connected AI platform leading financial institutions use to run their operations. We work with banks, lenders, credit unions, and other financial companies that lend money to people and manage those relationships over time. These institutions make millions of high-stakes decisions every day. Who should they reach? When should they reach them? What should they say or offer? When should a case move to a human? How should that change based on the borrower, the account, previous interactions, and the regulations involved? Getting those decisions right requires a deep understanding of the people, processes, rules, and edge cases behind them. Prodigal has spent the last eight years building that understanding. More than a billion interactions between financial institutions and their customers have shaped the intelligence, guardrails, and AI agents we now run in production across North America. Today, our AI agents analyze conversations, capture context, guide human agents, decide the next action, conduct customer conversations, orchestrate outreach, and help people complete payments and resolutions. They are connected, so what is learned in one interaction can inform what happens next. We are expanding this swarm of AI agents across more of the work financial institutions do: originations, document processing, back-office workflows, servicing, and other critical operations where money, identity, people, and regulation intersect. We are backed by Y Combinator, Accel, and Menlo Ventures, and work with 100+ financial institutions across North America. Listen directly from our CTO, Cofounder - Sangram Raje About the Role We're looking for an AI Engineer to join the proAgent team and work on the systems that power our autonomous voice agents in live financial conversations. You'll work alongside a small, high-agency team where you will have real ownership over features and components from day one. This is a hands-on engineering role. You'll be de
About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. The Ramp Revenue team is building an AI-native operating system for Go-to-Market teams. We turn fragmented customer context, communication history, and business signals into trusted agents that can identify opportunities, recommend actions, and execute real revenue work. This is a frontend-focused role for an engineer who obsesses over interaction design and complex product workflows, but is just as comfortable shaping the APIs and data contracts behind them. You’ll own the surfaces revenue teams actually use: agent-generated work, account and opportunity intelligence, approvals, workflow configuration, and execution experiences that bring together customer data, AI reasoning, and human judgment. If you want your frontend work to sit at the center of production agent systems—rather than being added after the intelligence and workflow decisions have already been made—this is the role. What You’ll Do Design and ship AI-native revenue products end to end, from React interfaces through the APIs and data contracts behind them. Build fast, information-den
We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart’s Commercial Scaled Intelligence (CSI) team is an AI-first group focused on turning data into action—building products that drive revenue growth, operational efficiency, and better outcomes for our customers, shoppers, retailers, brands, and partners. As the Ads AI Analytics Lead, you will own the intelligence behind our Ads agents. You’ll design the semantic and context layer for advertising, and build production-grade agents that analyze campaigns, diagnose performance, and recommend actions that improve ROAS, pacing, and partner outcomes. You will collaborate closely with Ads GTM, Product, Data Science, and Engineering to ship vertical agents with measurable lift. This seat is uniquely high-impact: the tools you build are used daily by Sales, Brand Partnerships, and Ads teams, including a sales tool used by approximately 265 sellers. Yo
Job Overview: We are looking for a Senior GenAI Developer to design, build, and productionize agentic AI systems—LLM-powered agents that can plan, use tools, orchestrate workflows, and operate reliably under enterprise constraints. You will own key parts of the agent architecture (planning, tool use, memory, evaluation, safety/guardrails, and observability) and deliver end-to-end solutions across RAG, function/tool calling, multi-agent coordination, and scalable deployment. Key Responsibilities Design and implement agentic systems: single-agent and multi-agent architectures (planner/executor, supervisor-worker, routing, reflection, critique, task decomposition). Build robust tool-using agents: function calling, tool schemas, tool authorization, retries, rate limiting, and sandboxing. Implement RAG + memory patterns: retrieval strategies, hybrid search, context assembly, long-term memory, and grounding/citation behaviors. Develop workflow orchestration for agent execution (state machines/graphs), concurrency controls, and deterministic execution where possible. Productionize GenAI services: APIs, background jobs, streaming responses, caching, and cost/latency optimization. Establish agent evaluation: golden sets, simulation-based evals, LLM-as-judge with mitigations, task success metrics, regression testing. Build observability and safety: tracing, token/tool telemetry, anomaly detection, prompt injection defenses, data leakage prevention, policy enforcement. Collaborate with product, security, and platform teams to deliver enterprise-ready solutions and integrate with internal systems (data, identity, workflow). Mentor engineers, set coding standards, and contribute to architecture reviews and technical roadmaps. Required Qualifications 6+ years software engineering experience; 2+ years building LLM/GenAI systems in production. Strong programming skills in Python (required) and/or TypeScript/Node.js. H
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
We are seeking passionate and driven individuals with a strong foundation in computer science to join our team. In this role, you'll have the opportunity to design, build, and test software that enhances MongoDB products while solving complex technical challenges. You’ll collaborate with cross-functional teams, balance innovation with delivery, and contribute to features that empower our global community of users. Join us in a supportive and inclusive environment that values your unique perspective and fuels your growth. We are looking to speak to candidates who are based in Dublin for our hybrid working model. What we are looking for in you In the process of receiving or having received a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field Recent graduates (including Summer 2026) or professionals with up to 18 months of experience. Have a foundation in computer science theory, with competencies in data structures, algorithms, and software design Proficient in one of our commonly used languages which include C++, Go, Ruby, Python, Java, Javascript, Node.js, or comparable high level programming languages Experience writing and testing software whether as part of an internship, in a personal project, in a coding competition, or for research What you'll find at MongoDB Writing and testing software in commonly used high level programming languages, such as C++, Go, Ruby, Python, Java, Javascript, Node.js Identifying, designing, testing, and supporting new features in MongoDB products, particularly utilizing competencies in data structures, algorithms, and software design Leading software projects that help users maintain and understand their MongoDB deployments Solving problems with context in mind, balancing the needs of the team with the desire to get to the bottom of issues Maintaining a balance between delivering software and performing research and development Working closely with cross functional teams to create end user fea
Senior Designer, Visual Interaction Design In a nutshell: We’re looking for a Senior Visual Interaction Designer to join our Cambridge Studio who is passionate about crafting elegant, thoughtful user experiences, and who brings strong visual design craft to the interactions people have with complex design systems, software, services, and each other. Senior Visual Interaction Designers at IDEO shape how experiences look, feel, and behave. In this role, you’ll translate human-centered insights into clear, compelling interactions and interfaces that are functional, expressive, and meaningful. You’ll balance visual excellence with usability, and bring a distinct visual voice to each design challenge while learning and growing alongside a multidisciplinary team. This is a phenomenal opportunity for designers who are highly self-guided, eager to take on complexity, and motivated to continually sharpen their craft. Once here you will: Contribute to a diverse portfolio of projects spanning data, experience, interaction, digital product, and service design across a range of industries Work across all phases of a project, from research synthesis and concepting through prototyping, refinement, and production-ready execution Translate human-centered insights into interaction models, visual systems, and polished digital interfaces Create “looks-like / works-like” prototypes to explore ideas, test assumptions, and communicate concepts to teammates and client stakeholders Collaborate closely with designers from different backgrounds—including design research, business design, industrial design, and communication design—to develop cohesive, holistic experiences Design across a wide variety of mediums and contexts, such as mobile apps, AI experiences, websites, digital/physical systems, room-scale displays, AR/VR, or voice interfaces, always guided by user needs and context Advocate for high-quality visual and interaction design, contributing to a culture of strong craft, curiosity,
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 evolving the Product Support experience, powered by AI, automation, and integrated systems. The AI Infrastructure & Tooling team helps make that possible by building intelligent, resilient, and integrated solutions that automate workflows, connect systems, and streamline support operations. As a Support Engineer, AI Infrastructure on this team, you'll be the technical execution layer that brings our support tools, customer and account context, internal systems, and AI workflows together. You'll design, build, and operationalize integrations across systems like Decagon, Zendesk, Figma admin tooling, and adjacent Product Support platforms. Your work will help us bring the right context into customer conversations, automate complex workflows, and optimize both the customer and Specialist experience by applying AI where it can meaningfully improve support workflows, quality, and efficiency. This role is ideal for someone who can move from ambiguous support problems to working technical solutions: understanding the workflow, identifying the systems involved, building the integration or automation, validating the data flow, and measuring the impact on customer outcomes and Specialist efficiency. 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: Build and operationalize AI-powered workflows that improve Product Support experiences for customers and internal support teams Design and maintain integrations across Decag
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 evolving the Product Support experience, powered by AI, automation, and integrated systems. The AI Infrastructure & Tooling team helps make that possible by building intelligent, resilient, and integrated solutions that automate workflows, connect systems, and streamline support operations. As a Support Engineer, AI Infrastructure & Tooling on this team, you'll be the technical execution layer that brings our support tools, customer and account context, internal systems, and AI workflows together. You'll design, build, and operationalize integrations across systems like Decagon, Zendesk, Figma admin tooling, and adjacent Product Support platforms. Your work will help us bring the right context into customer conversations, automate complex workflows, and optimize both the customer and Specialist experience by applying AI where it can meaningfully improve support workflows, quality, and efficiency. This role is ideal for someone who can move from ambiguous support problems to working technical solutions: understanding the workflow, identifying the systems involved, building the integration or automation, validating the data flow, and measuring the impact on customer outcomes and Specialist efficiency. 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: Build and operationalize AI-powered workflows that improve Product Support experiences for customers and internal support teams Design and maintain integr
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. The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems.&n
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. The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems.&n
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