At Magic, we are on a mission to create safe AGI that propels humanity forward in tackling the world's most pressing challenges. We believe that the key to achieving safe AGI lies in automating research and code generation, allowing us to enhance models and ensure alignment more reliably than human capabilities alone. Our innovative approach integrates frontier-scale pre-training, domain-specific reinforcement learning, ultra-long context, and advanced inference-time computing to realize this vision.About the Role:We are seeking a passionate individual to spearhead developer experience and data tooling within our pre-training data team. This role involves creating internal tools and infrastructure that enhance team productivity, including dashboards, command-line interfaces (CLIs), data exploration UIs, and the systems that interconnect them.Focusing on developer experience and tooling, we need someone who enjoys solving problems, deploying solutions quickly, and experimenting with new ideas.Potential Projects:Lead tooling initiatives across the architecture: develop systems, implement continuous integration, create CLI utilities, and design internal web interfaces.Design internal tools for dataset exploration, data labeling, quality assessment, and data inventory management.Enhance data infrastructure ergonomics—optimizing IO patterns in Ray/dataflow jobs, improving dataset tracking, and enhancing pipeline observability.Spot opportunities by engaging with the team, understanding their challenges, and proactively refining workflows.Elevate standards for code organization, packaging, and engineering best practices.What We Are Looking For:Preferred QualificationsSolid foundation in software engineering principles.Genuine interest in developer experience and best practices for code organization.Effective communicator, adept at collaborating with teammates to understand their requirements.Proactive mindset—identifies issues and implements solutions.Local to San Francisco (this role requires in-office attendance).Ideal Background (in order of importance)Open source contributor—experience with tools similar to Ruff, uv, or other developer-centric projects.Experience in build systems and CI—has developed or overseen build systems, CI pipelines, or developer tools on a large scale.Data pipeline experience—understanding of optimizing data workflows and data handling.

Join Anchorage Digital in revolutionizing the world of digital assets for institutional investors.Founded in 2017, Anchorage Digital is at the forefront of the regulated crypto space, offering a comprehensive platform that integrates financial services and infrastructure solutions. As the first federally chartered crypto bank in the United States, we deliver an unmatched combination of secure custody, regulatory compliance, extensive product offerings, and exceptional client service. We are eager to expand our team with talented individuals who are humble, innovative, and driven to grow.Our global team thrives in a remote-friendly environment, with options to work from our offices located in New York City, Sioux Falls, Porto, Lisbon, and Singapore. For those not close to our offices, we actively promote collaboration through quarterly in-person meetups to foster community and teamwork.As a pivotal member of the Data Platform team, you will contribute to the development of our Trusted Data Platform, facilitating Anchorage's journey towards Data 3.0. You will play a crucial role in shaping a unified orchestration foundation, implementing governance-as-code methodologies, and enhancing self-service frameworks to ensure automatic quality and compliance. Say goodbye to manual processes and embrace automated control planes where every dataset is inherently trusted, monitored, and traceable.To support our growth and impact measurements, we've established the Factors of Growth & Impact, designed for our team members to effectively assess their contributions and development while navigating the rich learning experiences within and beyond our team.

Our MissionAt Reflection AI, our mission is to create open superintelligence and ensure its accessibility for everyone.We are crafting open weight models for individuals, organizations, and even nations. Our talented team comprises AI researchers and entrepreneurs hailing from renowned institutions such as DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic, and more.FoundationsVision:Establish and maintain a comprehensive company-wide foundations platform that empowers every team by delivering dependable, scalable developer infrastructure, Site Reliability Engineering (SRE) capabilities, and high-throughput data ingestion tools, enabling Reflection to accelerate as we grow.What This Team DoesWe are responsible for developing and managing the essential data systems and pipelines that fuel our research, training, and production environments. This platform facilitates rapid experimentation, reliable model development, and scalable production workflows by integrating ingestion, processing, and orchestration throughout the data lifecycle.Design ingestion and orchestration patterns for both batch and streaming data workloads.Construct scalable compute and storage foundations (formats, engines, runtimes) that support extensive data processing.Guarantee reproducible pipelines through versioning, backfills, and isolated execution environments.Deliver trusted data quality, lineage, and governance signals to empower teams in making informed production decisions.Sustain predictable cost and performance through established guardrails, budgets, and ongoing system optimization.Facilitate a unified data layer that supports research, training, and production across the model development lifecycle.About the RoleYou will play a pivotal role in constructing the core data systems and pipelines that drive our research, training, and production environments. Your responsibilities will include designing and implementing reliable, scalable ingestion and orchestration patterns for batch and streaming workloads, developing storage and compute foundations that enable reproducible experimentation and rapid iteration, and establishing data quality and governance standards that teams can rely on for production decisions. You will also provide the foundational data layer that unifies ingestion, processing, and workflow management throughout model development.

NOTE: If you have previously submitted your application for any of our Research Engineer/Scientist, Machine Learning Research Engineer/Scientist, or Research Stream Lead positions, there is no need to reapply. We are consolidating all incoming applications for research roles into this single listing. About METRMETR is a pioneering nonprofit research organization dedicated to developing scientific methodologies that assess AI capabilities, risks, and mitigation strategies, particularly focusing on the threats posed by autonomy, AI R&D automation, and alignment. We believe that it is fundamentally beneficial for society to gain a clearer understanding of the potential dangers of AI systems, and we are eager to welcome passionate and talented individuals to our team to address one of the most pressing challenges of our time. Candidate evaluations primarily occur through practical work assessments. While we typically conduct in-person trials, we can offer flexibility in this regard. Position OverviewAt METR, we have three core research streams:Capabilities: We focus on accurately measuring the performance of frontier models on threat-relevant tasks (such as autonomy and AI R&D automation) and predicting future capabilities. Our work involves developing and maintaining benchmarks, diverse evidence-gathering techniques, and metrics to monitor capability trends and identify critical safety thresholds.Monitorability: Our aim is to understand how effectively frontier models can perform subversive or unwanted actions despite established monitoring and control protocols. We build the necessary research infrastructure—novel metrics, control evaluations, and elicitation methods—to enhance global understanding of how current and future models may evade oversight.Alignment/Propensity: We investigate whether models capable of causing catastrophic harm in their deployment contexts would likely do so in high-stakes scenarios. Our goal is to advance the science of propensity evaluations and explore conditions that may lead to significant catastrophic misalignment.The Capabilities and Monitorability streams are currently looking to hire Research Individual Contributors (ICs), while the Alignment/Propensity stream is seeking a Research Stream Lead, with plans to hire additional Research ICs in the future. The stream you join will be determined by a combination of your skills, interests, and fit within our team.

Overview: Join Listen Labs as we embark on an exciting journey to revolutionize decision-making for companies through cutting-edge AI technology. With a robust product roadmap planned for the next six months, we are expanding our engineering team. We are in search of a highly technical individual who thrives on solving complex problems and is eager to contribute to our mission. If you are passionate about innovation and want to be part of a team that includes several IOI medalists, we want to hear from you!About Listen Labs:Listen Labs is at the forefront of AI-powered research, enabling teams to extract valuable insights from customer interviews in a matter of hours rather than months. Our platform assists users in analyzing conversations, identifying key themes, and making informed product decisions swiftly.Why Join Us?Exceptional Team: Our founding team consists of seasoned entrepreneurs with a proven track record in AI, alongside top talents from renowned organizations such as Jane Street, Twitter, Stripe, and Goldman Sachs.Rapid Growth: Backed by Sequoia Capital, we have grown from zero to a $14M run-rate in under a year, with a dedicated team of 40.Impressive Clientele: We are witnessing significant traction across various sectors, securing enterprise clients like Google, Microsoft, and Nestlé.Product Excellence: Our differentiated product offers an industry-leading win rate, which is a testament to our commitment to quality.Market Success: Our customer base is expanding rapidly, with numerous six-figure contracts leading to further growth.Viral Impact: Our product's interviews reach tens of thousands of viewers, driving organic growth and interest from Fortune 500 companies.

Join Anchorage Digital in shaping the future of digital assets for institutional clients.Founded in 2017, Anchorage Digital stands as a pioneering regulated cryptocurrency platform, empowering institutions to engage seamlessly in the crypto ecosystem. As the first federally chartered crypto bank in the United States, we deliver an exceptional blend of secure custody, regulatory compliance, expansive product offerings, and outstanding client service. We aim to enrich our team with individuals who are humble, innovative, and eager to grow.Our remote-friendly, global workforce provides flexibility, but we also offer opportunities to work from our vibrant offices in New York City, Sioux Falls, Porto, Lisbon, and Singapore. For those not near our locations, we facilitate and sponsor quarterly in-person collaboration days to strengthen our community.As a member of the Asset Data team, you will play a crucial role in constructing the streaming data infrastructure that fuels Anchorage's digital asset platform. Your responsibilities will include designing systems that ingest real-time blockchain and market data from various sources, transforming raw inputs into verified, reliable data products. We are focused on developing contract-governed supply chains that allow rapid onboarding of new assets and data providers, while ensuring the low-latency and high-availability service levels that our business requires.We have established the Factors of Growth & Impact framework to assist our team members in effectively measuring their contributions and articulating the coaching, feedback, and enriching learning experiences that arise as they explore, develop, and master their roles within and beyond the Asset Data team.

About Contextual AI At Contextual AI, we are at the forefront of transforming the functionality of AI Agents by addressing one of the most significant challenges in artificial intelligence: context. By providing the right context at the right moment, we enhance the precision and scalability that enterprises leveraging AI demand. Our comprehensive enterprise AI development platform bridges the gap between groundbreaking AI research and the practical needs of developers. It empowers AI developers to efficiently ingest and query documents from various enterprise data sources, seamlessly integrating retrieval results into their business processes. Founded by the trailblazers of Retrieval-Augmented Generation (RAG), the core technique that connects foundational models to real-time, relevant information, Contextual AI is supported by visionary venture capitalists. We are not merely participants in the enterprise AI revolution; we are shaping its direction. Join us in crafting a future where AI not only answers inquiries but also revolutionizes business operations. About the Role As a Research-focused Member of Technical Staff, you will engage in pioneering AI research initiatives, contributing significantly to the development of Contextual RAG pipelines, including retrieval systems, language models, and alignment methodologies. Responsibilities Lead research projects in language modeling, retrieval, alignment, retrieval-augmented generation, end-to-end training, and evaluation. Develop and implement scalable infrastructure and tools that facilitate effective research and model development. Continuously review and stay informed about current literature, advancements, and industry best practices. Participate in the entire research pipeline, from ideation and experimentation to analysis and deployment. Publish research findings that contribute novel insights to the field of AI. Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related field; Master's or PhD preferred. Solid software engineering fundamentals with a proven history of developing complex systems. Deep understanding of core machine learning principles with hands-on experience in language modeling, retrieval, large-scale training, or evaluation. Research experience (academic or industry) is highly advantageous, including knowledge of experimental design, analysis, and research methodologies. Exceptional problem-solving capabilities and the ability to excel in a dynamic research environment.

About UsAt Odyssey, we are at the forefront of artificial intelligence, specializing in pioneering general-purpose world models that represent a groundbreaking form of multimodal intelligence. These innovations unlock a plethora of applications across consumer, enterprise, and intelligence sectors. Our flagship model, Odyssey-2 Pro, exemplifies our commitment to leading this revolutionary frontier.Position OverviewWe are seeking a seasoned Data Platform Lead who will take charge of our data practices. This pivotal technical leadership role emphasizes architectural strategy and execution. The ideal candidate will possess robust data engineering skills, adept at defining a long-term architectural vision while engaging directly with coding tasks. A comprehensive understanding of the data lifecycle is essential, from collaborating with Operations for data sourcing to designing efficient data processes that optimize our world models.Key ResponsibilitiesDefine and implement the long-term technical architecture for our data platform, ensuring scalability and reliability for high-volume, multimodal datasets.Manage the complete data lifecycle from sourcing to delivery for machine learning model training.Design and construct resilient data processing pipelines, focusing on data cleaning, feature engineering, and normalization tailored for world models.Oversee the data curation system, including adaptable metadata schemas, evolving labels, and modular tagging pipelines for effective data categorization and resampling.Collaborate closely with ML Research and Engineering teams to ascertain current and future data needs, translating research requirements into actionable data infrastructure and acquisition strategies.Lead the integration of advanced quality filtering and signal analysis into the data workflow, ensuring datasets meet rigorous quality standards.Drive data acquisition strategies by evaluating various methods, aligning with budgetary constraints and quality requirements.

At Stuut AI, we are revolutionizing accounts receivable for B2B companies, enhancing collections to be smarter and more efficient. Our platform is increasingly being adopted by finance teams in various sectors, including industrials, chemicals, and manufacturing, with clients ranging from Fortune 10 enterprises to growing midmarket firms. Our innovative approach is supported by esteemed investors such as Andreessen Horowitz, Khosla Ventures, Activant, 1984 Ventures, and Page One.Position OverviewWe are seeking a dedicated Technical Staff Member focused on Internal AI Tooling. This pivotal role will involve constructing the foundational systems that allow Stuut to scale effectively. Your primary responsibility will be to design and implement internal infrastructures, automation, and AI-driven workflows to enhance operational efficiency across various departments, starting with marketing and extending to sales, operations, and product development.This is a significant role for a proactive individual who thrives on transforming manual or disjointed processes into scalable systems. Collaboration with leadership and cross-functional teams will be essential as you design AI agents, automation pipelines, and internal tools that streamline operations and unlock new capabilities.We are transitioning to an agent-first model, not only in our products but also in our operational approach. This role is central to that evolution.

Role overview The Technical Staff Member (Data) - World Models position at Reka centers on building and maintaining large-scale data systems for AI model training. This role can be based in the US, Singapore, or remote. The focus is on integrating and processing petabyte-scale multimodal datasets, ensuring data infrastructure is both sustainable and efficient. What you will do Lead the development of data pipelines and storage solutions to handle vast and varied datasets for model training. Create automated, resource-efficient tools and systems that process diverse small datasets at scale. Design, automate, and maintain Python ETL pipelines (using Spark or Ray) for large multimodal data processing. Develop and maintain systems for data cataloging, lineage tracking, quality assurance, integrity checks, access management, and lifecycle oversight. Support colleagues by providing internal tools, documentation, and guidance on data best practices. Act as the primary steward of the organization’s datasets, ensuring their quality, accessibility, and overall health. Key challenges Build high-performance pipelines that process petabyte-scale datasets across thousands of CPUs and hundreds of GPUs. Adapt data formats, storage, and processing methods to keep pace with AI advancements while maintaining backward compatibility. Scale data infrastructure to support rapid organizational growth. Ensure the platform remains flexible for handling heterogeneous datasets and ad-hoc analytics needs. Requirements Expertise in data engineering, especially with Python ETL pipelines and familiarity with infrastructure, data formats, and large-scale storage systems. Experience in managing datasets, annotations, and data versioning for machine learning model training. Solid understanding of fundamental machine learning concepts to collaborate effectively with researchers and inform platform decisions. Ability to draft clear specifications for AI agents and maintain strong human oversight of AI-generated outputs. Demonstrated initiative, ownership, and effective communication in managing workload and priorities.

About PhyloPhylo is a pioneering applied research laboratory dedicated to the advancement of agentic intelligence aimed at accelerating the discovery process for biomedical scientists. We envision a future where AI agents revolutionize biomedical research, fostering rapid and systematic scientific advancements.Our expanding team consists of elite researchers and engineers specializing in AI and biology. With a robust $13.5M seed funding round led by top-tier investors such as a16z, Menlo Ventures, and Anthropic, and endorsed by Nobel Prize winners and leading biologists, Phylo is at the forefront of developing next-generation AI systems for the life sciences.About the RoleWe are seeking a skilled engineer to construct and maintain the essential systems that drive Phylo’s agentic AI platform in live environments. You will architect and implement distributed systems, computing frameworks, and service architectures that ensure our AI agents operate reliably at scale, whether in cloud-native settings or enterprise environments.This position represents a foundational role within our team, granting you substantial ownership over critical infrastructure decisions, a high level of autonomy, and the opportunity to significantly influence the company’s trajectory from day one.Our engineering team is AI-driven, leveraging coding agents extensively, moving swiftly, and maintaining rigorous standards of engineering excellence.ResponsibilitiesDesign and develop production systems that orchestrate agent execution and support AI-driven scientific workloads.Construct and manage scalable, reliable infrastructure across cloud, hybrid, and on-premises enterprise environments.Oversee enterprise deployment architecture, ensuring secure, reproducible installations for customer-managed infrastructures (VPC, private cloud, on-prem, air-gapped, or regulated environments).Create systems for sandboxed execution, secure task isolation, and controlled computing environments. Design and implement foundational security, access control, and compliance mechanisms suitable for enterprise deployments.Collaborate closely with ML and scientific teams to convert computational workflows into robust, production-grade distributed systems.RequirementsA minimum of 3 years of industry experience in backend, infrastructure, or distributed systems engineering.Demonstrated proficiency in at least one programming language (e.g., Python, Go, Rust).

ChronosphereChronosphere is a leading observability platform tailored for the complexities of modern, containerized environments. We empower our clients by simplifying data management, optimizing costs, and accelerating issue resolution. On average, our platform reduces data volumes and associated costs by 60%, saving developers countless hours. Our innovative Fluent Bit-based Telemetry Pipeline streamlines observability and security log data by transforming logs at the source and routing them to any destination without vendor lock-in.Recognized as a leader by prominent analyst firms, Chronosphere is trusted by industry pioneers such as Snap, Robinhood, DoorDash, and Zillow. Discover more at Chronosphere.io. Connect with us on LinkedIn and X.About the RoleOrganizations invest in observability tools primarily to detect and rectify issues swiftly. This has been crucial for over 25 years. The Alerting Platform team is dedicated to delivering a prompt, reliable, and user-friendly experience for configuring, receiving, and reacting to alerts.Our users—software developers—depend on efficient troubleshooting to enhance their own users' experiences. We develop solutions that propose actionable next steps for investigation, helping to narrow down possibilities and quickly identify root causes. We are looking for skilled engineers who can create intuitive, fast, and dependable user experiences that empower software engineers to address incidents with confidence.

At Moonvalley, we are at the forefront of innovation, developing groundbreaking generative AI models that are set to revolutionize the entertainment landscape. Our flagship HD model, Marey, is uniquely crafted with exclusively licensed data, targeting professional applications in Hollywood and various business sectors.Our diverse team is a remarkable blend of talent from various industries, including top AI scientists from DeepMind, Google, Microsoft, Meta, and Snap, bringing decades of collective expertise in machine learning and computational creativity. We proudly operate the first AI-enabled movie studio in Hollywood, collaborating with celebrated filmmakers and visionary artists. Our partnerships extend to leading producers and creative global brands, and we have successfully secured over $100 million from prestigious investors such as General Catalyst, Bessemer, Khosla Ventures, and YCombinator. This is just the beginning of our journey.Key Responsibilities:As a Member of Technical Staff, you will engage in exciting projects including:Collaborating with academic advisors to integrate pioneering research into our offerings.Engaging in R&D initiatives focused on advanced computer vision models.Staying abreast of the latest advancements in machine learning and AI to enhance our products continuously.Working alongside cross-functional teams to define, design, and implement machine learning models and pipelines.Executing experiments, analyzing data, and refining models for optimal performance.Participating in rapid iteration cycles for training, fine-tuning, testing, and deploying models.Validating and iterating on machine learning models tailored to video and image processing.Effectively communicating with cross-functional teams to grasp requirements and offer technical insights.

Join Composio, where we are revolutionizing the infrastructure that empowers agents to seamlessly connect with the tools you utilize daily, including GitHub, Gmail, Notion, Salesforce, and more. Our dedicated team of engineers is tackling challenges from context management to search optimization, striving to create the most efficient bridge between your agents and their essential tools.Having secured a $25M Series A funding from Lightspeed, along with support from prominent angels such as Guillermo Rauch (CEO of Vercel), Dharmesh Shah (CTO of HubSpot), and Gokul Rajaram, we have experienced significant growth, tripling our ARR this year. Our customers range from fellow Y Combinator alumni to established companies like Wabi, Glean, and Zoom.Your ResponsibilitiesEnhance our platform primitives and APIs, including authentication, automatic refreshes, triggers, tool search, planning, and sandbox management.Oversee multiple runtimes for code execution across Lambdas and Firecracker.Optimize performance through tracing, CPU/heap profiling, database query enhancements, and workflow optimization.Collaborate closely with product engineering teams and customers to effectively manage their workloads and improve our product.Produce clear and comprehensive documentation.Essential QualificationsCore Platform Engineering Skills: Extensive experience in scaling backend distributed systems, maintaining reliable systems while delivering quickly, and managing multiple platform components simultaneously.AI Expertise: Familiarity with building and working with language models.Linux Proficiency: Comfortable working in a Linux environment.Effective Communication: Ability to write well-structured documentation and articulate complex ideas clearly.Interpersonal Skills: Cultivate trust and acknowledge areas for growth.Preferred QualificationsExperience with cloud infrastructure and serverless architecture.

Our MissionAt Reflection AI, our mission is to develop open superintelligence and make it available to everyone.We are creating open weight models that cater to individuals, agents, enterprises, and even nations. Our skilled team of AI researchers and innovators hails from leading organizations such as DeepMind, OpenAI, Google Brain, Meta, Character.AI, and Anthropic.About the RoleThe Compute Platform team at Reflection AI focuses on ensuring our compute layer is robust and highly available. Our K8s-based platform spans multiple neo-clouds, tackling complex systems challenges related to multi-cloud scheduling, node health, and performance debugging. You will collaborate closely with our training teams to design strategies for fault tolerance, health checks, and remediation processes.Key ResponsibilitiesCluster Management: Develop and maintain tools for automatic remediation, topology-aware scheduling, capacity planning, and expedited hardware debugging.Platform Engineering: Design and refine our cluster management stack to efficiently handle workloads across extensive multi-GPU fleets.Monitoring & Observability: Establish an all-encompassing monitoring system for the cluster, emphasizing durability and active performance benchmarking.Roadmap Execution: Prepare the infrastructure for next-gen GPU deployments and larger cluster sizes. In the long run, you will contribute to managing multi-cloud storage, petabyte-scale data replication, and optimizing GPU-to-GPU network performance.

Our MissionAt Reflection AI, our mission is to develop open superintelligence accessible to everyone.We are creating open weight models for individuals, enterprises, agents, and nation-states. Our diverse team includes AI researchers and industry veterans from leading organizations such as DeepMind, OpenAI, Google Brain, Meta, Character.AI, and Anthropic.FoundationsVision: We aim to establish and maintain a company-wide foundational platform designed to enhance every team by offering dependable, scalable development infrastructure, Site Reliability Engineering (SRE) capabilities, and high-throughput data ingestion tools. This enables Reflection to expedite its growth as we scale.What This Team DoesOur team builds and manages the essential platform layer that every engineering team relies on. We craft clear, opinionated golden paths for cloud infrastructure, networking, and access patterns, ensuring that the safest and most scalable routes are also the easiest to navigate. We work across various domains including cloud infrastructure, network primitives, security protocols, and developer tools to empower engineers to deploy rapidly while ensuring reliability, security, and cost predictability.Define and uphold golden paths for cloud projects and access patterns.Implement secure defaults and guardrails, making the safe path the most straightforward option.Construct and manage core networking components such as routing, DNS, load balancing, and connectivity.Establish baseline observability and operational best practices across services and infrastructure.Oversee developer infrastructure including build systems, CI/CD, caching, and testing infrastructure to facilitate rapid shipping.Enhance cloud cost visibility and reduction through effective tooling, guardrails, and optimization strategies without hindering team progress.What You'll Work WithCloud & Multi-Cloud Architecture: GCP, AWS, multi-cloud configurations, VPC architecture, private DNS, load balancers, advanced routing (BGP), and large-scale Kubernetes clusters.Identity & Security Foundations: IAM, OIDC, RBAC, KMS, secrets management, policy-as-code (OPA, Gatekeeper), secure defaults, and cloud guardrails.Infrastructure & Automation: Terraform, Pulumi, foundational Kubernetes, CI/CD systems, Bazel, build caching, and hermetic builds.Observability & Cost Governance: Prometheus, Grafana, OpenTelemetry, and more.

Overview: Due to the increasing market demand and a robust six-month product roadmap, Listen Labs is expanding its engineering team. We seek a technically adept individual (our team includes three IOI medalists) who is eager to contribute to a product that is revolutionizing corporate decision-making. If you are passionate about solving intricate problems from start to finish, we invite you to connect with us.About Listen LabsListen Labs is an innovative AI-driven research platform that empowers teams to swiftly extract insights from customer interviews in hours rather than months. Our technology enables clients to analyze conversations, identify recurring themes, and expedite informed product decisions.Company Highlights:Exceptional Team: Composed of seasoned entrepreneurs (with prior AI exits), co-founders, and experts from leading firms such as Jane Street, Twitter, Stripe, Affirm, Bain, Goldman Sachs, and more, our team is built on a foundation of excellence.Rapid Growth: We are a dynamic team of 40, supported by Sequoia, achieving a remarkable growth trajectory from $0 to $14 million run-rate in less than a year. We prioritize speed, craftsmanship, and collaboration with individuals who embrace ownership.Impressive Traction: We have seen rapid growth across various sectors, securing enterprise clients such as Google, Microsoft, Nestlé, and P&G.Outstanding Performance: Our industry-leading win rate is a direct result of our uniquely differentiated product.Market Validation: We consistently attract customers across every segment, often landing six-figure deals that lead to quick expansions.Viral Product: Our interviews are shared with tens of thousands of viewers, driving product-led growth, organic expansion, and daily inquiries from Fortune 500 companies.Technical Challenges:Research Agent Development: Unlike traditional software purchases, hiring McKinsey involves gaining insights and execution expertise. We are building Listen Labs with that mindset — an AI agent that understands our platform and best research practices, assisting users in project setup, interview execution, and response analysis.Human Database Creation: A core value proposition is our capability to connect users with specific demographics. We are developing a database of millions of individuals, continually enhancing our understanding of user needs as they engage with Listen Labs.

Overview: Listen Labs is experiencing robust market demand and is set to launch an ambitious product roadmap over the next six months. We are seeking an exceptionally technical individual to join our engineering team, which includes three IOI medalists. If you're passionate about building innovative solutions that empower companies to make informed decisions, we want to hear from you.About Listen Labs:Listen Labs is an advanced AI-driven research platform designed to help teams extract actionable insights from customer interviews in record time. Our technology enables users to analyze conversations, identify key themes, and expedite the decision-making process.Why Join Us?Exceptional Team: Our founders are seasoned entrepreneurs with successful AI exits, complemented by talent from prestigious firms like Jane Street, Twitter, Stripe, Bain, and Goldman Sachs, along with backgrounds in IOI/ICPC.Rapid Growth: As a 40-person team backed by Sequoia, we have scaled from $0 to a $14 million run-rate in under a year. We prioritize craftsmanship and collaborate with individuals who demonstrate ownership.Proven Success: Our traction includes significant enterprise wins with clients such as Google, Microsoft, Nestlé, and P&G.Market Leadership: Our product's unique features drive an industry-leading win rate and rapid customer acquisition across various segments.Viral Growth: Our interviews are disseminated widely, fueling organic growth and attracting attention from Fortune 500 companies.Technical Challenges:AI Research Agent: We are developing an AI research agent that transforms traditional research methodologies, offering expert guidance on project setup, interview strategies, and data analysis.Human Database: Our goal is to create a comprehensive database of users, enhancing our ability to connect clients with target demographics based on ongoing research studies.

Join xAI's innovative Platform Security team as a Technical Staff Member, where you'll develop state-of-the-art security solutions to safeguard our Kubernetes infrastructure and enhance secure AI systems. In this role, you will design and implement AI-driven security tools, proactively tackle vulnerabilities, and advocate for secure engineering practices. Ideal candidates are passionate about impactful innovation, excel in writing clean and efficient code, and thrive in fast-paced environments, all while supporting xAI’s mission to create a trusted and secure global digital platform.