Applied AI Engineer

About UsAt Applied Compute, we are pioneering the development of Specific Intelligence for enterprises, creating agents that continuously learn from a company’s processes, data, expertise, and objectives. Our mission is to bridge the gap between isolated AI capabilities and their effective application within real business environments. Traditional AI systems often fall short as they lack the ability to adapt based on feedback. Our innovative continual learning layer captures context, memory, and decision-making processes across the enterprise, enabling specialized agents to engage in meaningful work.What Excites Us: We operate at the exciting intersection of product development and cutting-edge research. Our product team designs the platform that empowers a new generation of digital coworkers, while our research team drives advancements in post-training and reinforcement learning to enhance user experiences. As an applied research engineer, you will work directly with clients to implement models in production, combining robust product development with deep research insights to facilitate AI integration in enterprises.Meet Our Team: Our diverse team consists of engineers, researchers, and operators, many of whom are former founders. We have previously built reinforcement learning infrastructure at OpenAI, established data foundations at Scale AI, and contributed to significant systems at companies like Together, Two Sigma, and Watershed. We collaborate with Fortune 50 clients, including DoorDash, Mercor, and Cognition, and are proud to be backed by reputable investors such as Benchmark, Sequoia, and Lux.Who Thrives Here: We seek individuals who are passionate about applying innovative research and complex systems to solve real-world challenges. You should feel comfortable navigating new environments rapidly—be it a fresh codebase, a client’s data architecture, or an unfamiliar problem domain. A genuine enjoyment for customer interaction, empathy, and a deep understanding of their operational workflows are essential. Candidates with entrepreneurial backgrounds, extensive side projects, or a proven track record of end-to-end ownership typically excel in our environment.

Join Our Innovative TeamAt OpenAI, we are pioneering the field of artificial intelligence, empowering innovation and shaping the future through transformative research. Our mission is to democratize AI, ensuring its benefits are accessible to all. We are on the lookout for forward-thinking Research Engineers to join our Applied Group, where you will convert groundbreaking research into practical applications that can revolutionize industries, enhance human creativity, and tackle complex challenges.Your Impactful RoleAs a Research Engineer within OpenAI's Applied Group, you will collaborate with some of the brightest minds in AI. Your work will involve deploying cutting-edge models in production settings, transforming theoretical breakthroughs into impactful solutions. If you are passionate about making AI technology accessible and effective, this is your opportunity to leave a significant impact.In this role, you will:Innovate and Deploy: Create and implement advanced machine learning models addressing real-world issues. Translate OpenAI's research from theory to practice, developing AI-driven applications that make a meaningful difference.Collaborate with Experts: Engage closely with researchers, software engineers, and product managers to comprehend intricate business challenges and deliver AI-based solutions. Become part of a vibrant team where creativity and ideas flourish.Optimize and Scale: Develop scalable data pipelines, fine-tune models for peak performance and precision, and ensure readiness for production. Contribute to projects that leverage state-of-the-art technology and innovative methodologies.Learn and Lead: Stay at the forefront of advancements in machine learning and AI. Participate in code reviews, share insights, and exemplify best practices to maintain high standards in engineering.Make a Difference: Oversee and maintain deployed models, ensuring they consistently deliver value. Your contributions will directly shape how AI benefits individuals, businesses, and society as a whole.You may excel in this position if you possess:A Master's or PhD in Computer Science, Machine Learning, Data Science, or a related discipline.Proven experience in deep learning and transformer models.Expertise with frameworks such as PyTorch or TensorFlow.A robust understanding of data structures, algorithms, and software engineering principles.Experience with cloud platforms and deploying machine learning models in production.

At Netic, we are revolutionizing the essential services sector with our advanced AI-driven revenue engine, which supports the backbone of the American economy.Backed by $43M in funding from illustrious investors such as Founders Fund, Greylock, Hanabi, and Dylan Field, who spearheaded our Series B, we have empowered our clients to secure hundreds of thousands of jobs across various service industries throughout North America. Our platform has enabled companies to operate with an AI-first approach.Join our innovative team of relentless builders hailing from renowned organizations like Scale, Databricks, HRT, Meta, MIT, Stanford, and Harvard. Together, we are applying frontier AI to solve complex challenges in the physical economy, where data is intricate and the results are both immediate and impactful.As an Applied AI Research Engineer, you will immerse yourself in pioneering research, gain a thorough understanding of the business functions we automate, and lead targeted machine learning projects that yield remarkable outcomes.

Join Our Innovative Team at ArcadeAt Arcade, we are revolutionizing the way physical products are created with our cutting-edge AI platform. We empower individuals to turn their creative ideas into tangible products seamlessly, utilizing natural language and generative AI. Our mission is to democratize product design, making it as effortless as sharing a post online.Backed by a remarkable $42M in funding from industry-leading investors including Reid Hoffman and Ashton Kutcher, our company is a rising star in the tech landscape. Guided by our founder Mariam Naficy and a team steeped in AI and design expertise, we are at the forefront of a new frontier that merges AI, personal expression, and on-demand manufacturing.Your Role as an Applied AI EngineerWe are on the lookout for an Applied AI Engineer to enhance our generative AI capabilities. This position combines hands-on model development with the integration of advanced AI techniques into our production systems. You will collaborate with diverse teams to conduct research, experiment with models, and implement AI-driven products.

Join fuku as an Applied Research Engineer in San Francisco, CA, where you will be at the forefront of AI video data research. As a crucial member of our team, your mission will involve building robust, high-performance frameworks and extensive pipelines to process and decode video data with exceptional accuracy. You will tackle complex research challenges, refine machine learning models and APIs, and deliver comprehensive solutions across computer vision, audio, and text processing domains. This role is designed for engineers who thrive in both research and production environments and are eager to spearhead the evolution of video understanding from research to deployment.

About HebbiaHebbia is an innovative AI platform designed specifically for investors and bankers, empowering them to generate alpha and unlock new opportunities.Founded in 2020 by George Sivulka and backed by industry leaders like Peter Thiel and Andreessen Horowitz, Hebbia supports investment decisions for major firms including BlackRock, KKR, Carlyle, Centerview, and accounts for 40% of the world's largest asset managers. Our flagship product, Matrix, is recognized for its unparalleled accuracy, speed, and transparency in AI-driven analysis, managing assets exceeding $30 trillion globally.We provide critical insights that give finance professionals a competitive advantage by revealing signals that are invisible to the human eye and identifying hidden opportunities while expediting decision-making with remarkable speed and certainty. We aim to revolutionize the way capital is allocated, risk is mitigated, and value is generated across markets.Hebbia is not just a tool; it is the competitive edge that enhances performance, alpha, and market leadership.The TeamOur Agents team is dedicated to building sophisticated reasoning, copiloting, and retrieval capabilities that unlock significant insights for real-world applications. We develop everything from foundational document understanding features to co-piloting experiences for matrix and extensive, multi-source research. Our proprietary agentic frameworks are designed for scalability, utilizing distributed systems.We focus on creating systems that are not only successful but also reliable, explainable, and adaptable for the vast data our clients encounter. Our mission is to unveil the unknowable unknown for customers worldwide.Our goal is to create a product that becomes indispensable to our users, offering an experience as delightful as their favorite consumer products. We prioritize swift innovation and the development of first-of-their-kind systems.

Join Scale AI as a passionate and technically adept AI Research Engineer within our Enterprise Evaluations team. This pivotal role is integral to our goal of providing the industry's leading Generative AI Evaluation Suite. You will actively contribute to the foundational systems that guarantee the safety, dependability, and ongoing enhancement of LLM-driven workflows and agents for enterprise clients. The perfect candidate will possess a robust understanding of large language models, a fervor for addressing intricate evaluation dilemmas, and the ability to excel in a fast-evolving research atmosphere. We seek an engineer who can innovate, remains informed about the latest studies in AI evaluation, and is enthusiastic about incorporating cutting-edge research concepts into our workflows to create top-tier evaluation systems.

Sieve is a 15-person AI research lab in San Francisco focused on video data. The team builds exabyte-scale video infrastructure and develops new approaches for video understanding, drawing from diverse data sources to create advanced datasets. With video now accounting for most internet traffic, Sieve aims to solve the challenge of delivering high-quality training data for applications in creativity, communication, gaming, AR/VR, and robotics. The company partners with leading AI labs and has achieved strong financial results, backed by Series A funding from Matrix Partners, Swift Ventures, Y Combinator, and AI Grant. Internship overview The Applied Research Engineering Intern will help build high-performance components and large-scale pipelines to advance video understanding at internet scale. This role involves tackling ambiguous research problems and turning them into practical solutions. Projects often cover computer vision, audio processing, and text processing. What you will do Develop and optimize models and APIs for video, audio, and text data Improve performance through pre- and post-processing, parallelism, pipelining, and inference optimization Occasionally fine-tune models for specific tasks Work through open-ended research challenges with a small, focused team Who succeeds here Comfortable working with machine learning models and APIs Skilled at optimizing systems for speed and accuracy Enjoys solving ambiguous technical problems across computer vision, audio, and text domains

About UsAt Applied Compute, we are pioneering Specific Intelligence for enterprises through advanced AI agents that learn continuously from organizational processes, data, and objectives. We recognize the significant gap between what AI models can achieve in isolation and their performance within actual business contexts, often failing to adapt to feedback. Our mission is to build a continual learning layer that captures context, memory, and decision traces across enterprises, creating environments where specialized agents excel at real tasks.Why Join Us? We operate at a unique intersection of product development and research. Our product team is developing the platform that empowers a new generation of digital coworkers, while our research team is advancing post-training and reinforcement learning to enhance product experiences. As applied research engineers, we work closely with customers to deploy models into production effectively. This blend of robust product focus, deep research, and customer engagement is our strategy for successfully integrating AI into enterprise operations. We are product-led, research-enabled, and strategically deployed.Meet Our Team: Our team consists of engineers, researchers, and operators, many of whom are former founders. We have established RL infrastructure at OpenAI, developed data foundations at Scale AI, and built systems at Together, Two Sigma, and Watershed. We collaborate with Fortune 50 clients, including DoorDash, Mercor, and Cognition, and are backed by esteemed investors such as Benchmark, Sequoia, and Lux.Who Excels Here: We seek individuals passionate about applying innovative research and complex systems to overcome real-world challenges. Candidates should thrive in unfamiliar environments, whether it involves navigating new codebases, understanding new customer data architectures, or tackling unfamiliar problem domains. A genuine enjoyment of customer interactions—listening, empathizing, and comprehending how work is accomplished within organizations—is essential. Those with prior entrepreneurial experience, extensive side projects, or a proven ability to manage initiatives from start to finish will thrive in our culture.Your RoleAs a Research Systems Engineer, you will be responsible for training cutting-edge models and developing methodologies that facilitate continual learning within enterprise settings. You will design and execute large-scale experiments, delve into advanced reinforcement learning techniques, and create tools that enhance our understanding of the training process. This role uniquely positions you at the crossroads of research and systems engineering, where you will innovate new algorithms in collaboration with researchers and work alongside infrastructure engineers to deploy them on GPUs.

Join Our Pioneering TeamAt Sieve, we are trailblazers in the realm of AI research, specifically dedicated to harnessing the power of video data. Our cutting-edge infrastructure processes exabyte-scale video, utilizing innovative video understanding methodologies, and integrating diverse data sources to create groundbreaking datasets that redefine video modeling. With video accounting for a staggering 80% of global internet traffic, it stands as the cornerstone of digital creativity, communication, gaming, AR/VR, and robotics. Our mission is to eliminate the primary barrier to the growth of these technologies: the scarcity of high-quality training data.Having collaborated with leading AI laboratories, we achieved $XXM in revenue last quarter alone with a compact team of just 15 talented individuals. Our successful Series A funding round last year, backed by prestigious firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant, underscores our potential for exponential growth.The Role You’ll PlayAs an Applied Research Engineer at Sieve, you will be instrumental in constructing high-performance building blocks and expansive pipelines to achieve high-precision video comprehension at internet scale. Your role will often involve tackling ambiguous research challenges and devising ingenious solutions. You will engage with domains including computer vision, audio processing, and text processing.The ideal candidate will possess a strong command of models and APIs, leveraging innovative pre/post-processing techniques, parallelism, pipelining, inference optimization, and occasional fine-tuning to maximize performance.

About Distyl AIDistyl AI specializes in creating high-performance AI systems that enhance the fundamental operational processes of Fortune 500 companies. Through a strategic alliance with OpenAI, proprietary software accelerators, and extensive expertise in enterprise AI, we deliver effective AI solutions with swift time-to-value, often within a quarter.Our innovations have empowered Fortune 500 clients in various sectors, including insurance, consumer packaged goods, and non-profit organizations. Joining our team means you will assist organizations in recognizing, developing, and extracting value from their Generative AI investments, frequently for the first time. We prioritize customer needs, working backward from the client's challenges and ensuring we generate financial benefits while enhancing the experiences of end-users.Distyl is guided by seasoned leaders from top-tier companies like Palantir and Apple and enjoys backing from prominent investors including Lightspeed, Khosla, Coatue, Dell Technologies Capital, Nat Friedman (Former CEO of GitHub), Brad Gerstner (Founder and CEO of Altimeter), along with board members from numerous Fortune 500 firms.What We Are Looking ForAt Distyl, we are at the forefront of leveraging AI within enterprises. We seek imaginative researchers who aspire to go beyond incremental enhancements on benchmarks and are eager to redefine the application of software in innovative ways.Our researchers hail from diverse academic disciplines but possess a robust research background, operate in an AI-centric manner, and would find conventional research environments unfulfilling.Key ResponsibilitiesThe AI Systems team is dedicated to architecting complex, comprehensive solutions that integrate perception, reasoning, planning, and execution. Researchers amalgamate various components (LLMs, retrievers, evaluators, memory systems, and execution agents) into resilient, scalable systems that deliver consistent performance across dynamic enterprise workflows.Researchers in AI Systems examine the principles governing intricate system interactions. They analyze coordination, information flow, and emergent behavior across multiple agents and models. Their research reveals the foundational mechanics of robustness, composability, and alignment, ultimately establishing the design paradigm for constructing intelligent systems.

About WorkOS WorkOS is revolutionizing the developer landscape by creating cutting-edge tools and APIs that empower businesses to achieve Enterprise Ready status. Our platform is the backbone for authentication, identity management, authorization, and other essential infrastructures, enabling developers to securely scale their products for large enterprises.Having recently secured a $100M Series C funding round, valuing the company at $2B, we are supported by leading investors such as Meritech, Sapphire, Greenoaks, Craft, Abstract, and Audacious. WorkOS is proud to serve many of the fastest-growing AI companies, including OpenAI, Cursor, Perplexity, Vercel, and Plaid.As AI technology evolves, WorkOS stands at the forefront of Human and Agent Authentication, Identity, and Access Control, helping businesses navigate crucial questions about agent identity and permissions. Our rapidly expanding customer base features hundreds of innovative software companies developing the next generation of enterprise-ready solutions.About the RoleWe are assembling an Applied AI team dedicated to significantly enhancing productivity across Engineering, Sales, Support, and Operations while also developing AI functionalities for our clients.As an Applied AI Engineer, you will design and deploy transformative AI systems that redefine how WorkOS develops, markets, and supports its software. You will focus on creating robust tools and workflows that are essential for daily operations, while also exploring novel AI capabilities for our users.Join a small, high-ownership team that:Identifies challenges based on measurable impact.Rapidly transitions from idea to prototype to production in days or weeks.Quickly adapts to evolving models, tools, and best practices.This role offers substantial visibility across the organization.What You’ll DoCollaborate closely with Engineering, Sales, Support, and Operations to identify high-impact internal challenges where AI can enhance efficiency or facilitate new workflows.Design and construct tools that integrate seamlessly into daily operations—agents, automations, and workflows that are reliable, observable, and easy to maintain.Leverage LLMs, embeddings, retrieval systems, and tool-calling to connect with documents, Slack, GitHub, CRM systems, analytics, support frameworks, and internal services.Transform repetitive, multi-step manual tasks into streamlined, AI-driven processes that span various applications and data sources.Stay informed about emerging models and tools, conduct focused experiments, and assist the team in continuous improvement.

WHO WE AREAt Applied Compute, we specialize in creating Specific Intelligence for enterprises—agents that continually learn from a company's processes, data, expertise, and goals. Our mission is to develop a continual learning layer and platform that captures context, memory, and decision traces across organizations, fostering an environment where specialized agents perform real work effectively.Why Join Us: We operate at a unique intersection of product development and advanced research. Our product team is building the platform for a new generation of digital coworkers, while our research team is pioneering advancements in post-training and reinforcement learning to enrich product experiences. Our applied research engineers collaborate closely with customers, deploying agents into production seamlessly. This blend of robust product focus, in-depth research, and real-world application is our approach to integrating AI into enterprises. We pride ourselves on being product-led, research-enabled, and forward-deployed.Our Team: We are a diverse group of engineers, researchers, and operators, many of whom are former founders with experience in RL infrastructure at OpenAI, data foundations at Scale AI, and various systems across renowned firms like Two Sigma and Watershed. We collaborate with Fortune 50 clients and are proudly backed by reputable investors including Kleiner Perkins, Benchmark, Sequoia, Lux, and Greenoaks.Who Thrives Here: We seek individuals passionate about applying innovative research and complex systems to solve real-world challenges. You should be adept at navigating new environments swiftly, whether it's a fresh codebase, a customer's data architecture, or an unfamiliar problem domain. Our team values collaboration with customers, emphasizing active listening and understanding their workflows. We find that former founders, individuals with extensive side projects, and those who demonstrate end-to-end ownership excel in our culture.THE ROLEIn the role of Research Systems Engineer, you will train frontier-scale models and devise methodologies to implement continual learning in enterprise settings. Your responsibilities will include designing and executing large-scale experiments, investigating cutting-edge reinforcement learning techniques, and developing tools to gain insights into training processes. This position lies at the crossroads of research and systems engineering, where you will innovate algorithms alongside researchers and collaborate with infrastructure engineers to implement them on GPUs.

About Us:At LangChain, we strive to revolutionize the accessibility of intelligent agents. Our goal is to provide a robust framework for agent engineering that empowers developers to transition from initial prototypes to production-ready AI agents that can be trusted by teams. What started as a suite of widely embraced open-source tools has evolved into a comprehensive platform designed for the building, assessment, deployment, and management of agents at scale.Currently, our tools, including LangChain, LangGraph, LangSmith, and Agent Builder, are utilized by various teams delivering tangible AI solutions across both startups and large corporations. Millions of developers depend on LangChain to empower AI initiatives at prestigious companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.With $125M raised in our Series B round from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we are in a phase of rapid growth, continuously innovating new products while ensuring every team member has a significant impact on our development and collaborative processes. LangChain is a place where your contributions can influence the real-world application of this transformative technology.About the Role:We are seeking talented Applied AI Engineers to assist in creating AI agents that enhance various aspects of LangChain, from Marketing and Go-To-Market strategies to Recruiting, Support, Internal Tools, and our Core Product.In this position, you will take ownership of specific problem areas, collaborating closely with relevant teams to design, construct, and deploy production-grade agents, workflows, and applications that revolutionize our operational processes. Your contributions will directly support LangChain’s vision of making intelligent, autonomous software a reality for both our internal teams and our clients. Some projects may be open source, contributing to the LangChain and LangGraph ecosystems while establishing new benchmarks for AI development practices.If you are a full-stack software engineer eager to implement AI agents in practical use cases and witness their impact on business outcomes, we invite you to apply.

Quizlet Inc. is looking for an Applied AI Engineer to create AI-driven features that support student learning. This position centers on developing and deploying machine learning solutions aimed at making study experiences more effective and engaging for a global user base. What you will do Design and implement machine learning models to enhance Quizlet’s educational tools Work on features that help students study more efficiently and enjoyably Locations Denver, CO New York, NY San Francisco, CA Seattle, WA

Join Our Team as an Applied AI EngineerAt Rowspace, we're at the forefront of AI research and engineering, and we are looking for an Applied AI Engineer to help revolutionize how our platform uncovers vital financial insights. Your week may involve developing and deploying AI agents based on client feedback, creating evaluation frameworks for AI performance, and designing sophisticated retrieval systems to optimize AI within financial workflows.Your ResponsibilitiesIntegrate groundbreaking AI research to develop systems that comprehend financial contexts and business concepts.Construct retrieval pipelines that intelligently extract and synthesize insights from unstructured data sources such as PDFs, emails, and presentations.Develop workflows that empower AI systems to analyze financial relationships, conduct benchmarking, and perform comparative analyses.Design and maintain knowledge graphs that represent intricate financial relationships, entity connections, and market dynamics.Create evaluation frameworks to assess and enhance AI performance in investment research, due diligence, and portfolio monitoring.Implement systems ensuring traceability from AI outputs to primary data sources.Experiment with innovative LLM orchestration patterns and context management techniques tailored for financial applications.Guide the technical direction and establish best practices for AI application development at Rowspace.Engage in rapid iteration with direct customer feedback to continuously enhance AI systems based on real-world usage.Oversee the deployment and operation of production systems end-to-end, ensuring reliability, performance, and maintainability across the technology stack.

About Komodo Health We Bring Data to Life Komodo Health’s mission is to alleviate the global burden of disease. The company’s Healthcare Map integrates de-identified patient data with advanced algorithms and clinical expertise, creating a detailed view of the U.S. healthcare system. This foundation supports a suite of software applications that help partners address complex healthcare challenges, monitor patient behaviors, spot treatment trends, and identify care gaps. Komodo Health values excellence, growth, results, and enjoying the journey. The team brings together professionals from varied backgrounds who share a commitment to improving health outcomes. Role Overview: Applied AI Engineer Healthcare in the U.S. is intricate, and Komodo Health tackles these challenges through data-driven solutions. By mapping the patient journey nationwide, the company helps pharmaceutical firms, payers, and healthcare systems make decisions that improve patient care. Labs@Komodo builds AI-native platforms and systems that turn data into actionable insights. The team developed Marmot, Komodo’s AI-native product, which embeds AI into both the user interface and development workflow. By combining Komodo’s healthcare data with modern large language models (LLMs), Marmot delivers real-world insights for healthcare stakeholders. What You Will Do Design and implement end-to-end AI solutions for real products and internal tools. Work at the intersection of applied research, engineering, and product development. Integrate modern AI techniques into scalable, production-ready systems. Collaborate with product, platform, and data teams to build AI capabilities that advance healthcare data use. Location San Francisco, CA

About the Role sfcompute is hiring an Applied AI Engineer in San Francisco, CA. This position focuses on building and deploying AI models that support real business needs. The work involves using advanced technologies to create practical solutions that improve how teams operate. What You Will Do Develop and implement AI models tailored to business goals Work closely with teams across the company to understand their challenges Deliver solutions that boost productivity and efficiency

About GranicaGranica is an innovative AI research and infrastructure firm dedicated to creating reliable, steerable representations of enterprise data.We establish trust through Crunch, a policy-driven health layer optimizing large tabular datasets for efficiency, reliability, and reversibility. Utilizing this foundation, we are developing Large Tabular Models—systems designed to learn cross-column and relational structures, delivering trustworthy answers and automation with integrated provenance and governance.Our MissionCurrent AI capabilities are hindered not only by model design but also by the inefficiencies of the data that supports it. At scale, each redundant byte, poorly organized dataset, and inefficient data pathway contributes to significant costs, latency, and energy waste.Granica’s mission is to eliminate these inefficiencies. We leverage groundbreaking research in information theory, probabilistic modeling, and distributed systems to craft self-optimizing data infrastructure: systems that continually enhance how information is represented and utilized by AI.Led by Prof. Andrea Montanari from Stanford, Granica’s Research group merges advances in information theory with learning efficiency in large-scale distributed systems. We collectively believe that the next significant leap in AI will originate from innovations in efficient systems, rather than merely larger models.Granica is at the forefront of developing a new category of structured AI models: foundational models designed to learn and reason from the relational, tabular, and structured data that drives the global economy. While many focus on unstructured text or media, we are venturing into the next frontier: systems capable of comprehending and reasoning over structured information.Your ContributionsCreate and prototype algorithms that form the core of structured AI, enhancing representation learning and efficient information modeling for enterprise and tabular data at petabyte scale.Develop adaptive learners merging statistical learning theory with systems optimization at scale, contributing to a new generation of foundational models for structured information.Design architectures that unify symbolic, relational, and neural components, enabling AI systems to reason directly over structured enterprise data.Construct cost models and optimization frameworks that enhance the efficiency of structured learning, both computationally and economically.