Applied Research Engineer

About Our TeamAt OpenAI, we are dedicated to extending the reach of our advanced AI technology through innovative products like ChatGPT and the OpenAI API. Our mission is to learn from deployment and share the benefits of AI, while prioritizing safety and responsible usage over unchecked growth.Role OverviewWe are on the lookout for a seasoned Research Engineer to spearhead efforts in retrieval and search across our API and ChatGPT platforms. As the AI landscape continues to evolve, retrieval and search capabilities have emerged as pivotal for our models. You will play a crucial role in developing search-based product experiences that will impact millions of users globally.In this position, your responsibilities will include:Collaborating closely with our research team to advance retrieval and search algorithms across various domains such as document search, enterprise search, knowledge retrieval, and web-scale search.Implementing these search methodologies into production for both the API and ChatGPT, enhancing user experiences for millions.Investigating cutting-edge research topics in retrieval and search to inform our product strategy for the future.Working together with researchers, engineers, product managers, and designers to introduce new features and innovations.Ideal Candidate ProfileYou will thrive in this role if you:Possess substantial experience in building and maintaining production-level machine learning systems.Have a background in working with vector databases, search indices, or other data storage solutions tailored for search and retrieval applications.Are proficient in developing and refining internet-scale search systems.Exhibit a strong sense of ownership over projects and are eager to acquire new skills to tackle challenges effectively.Demonstrate the ability to work swiftly in an environment with evolving parameters and competing priorities.

Join Firecrawl as a Research Engineer focusing on Search and Information Retrieval (IR). In this pivotal role, you will leverage cutting-edge technologies to develop innovative solutions that enhance our clients' search capabilities. You will work closely with cross-functional teams to analyze data, implement algorithms, and contribute to the advancement of our search platforms.

About Our TeamJoin the Foundations Research team, where we tackle ambitious and innovative projects that could redefine the future of AI. Our mission is to enhance the science behind our training and scaling initiatives, focusing on pioneering frontier models. We are dedicated to advancing data utilization, scaling methodologies, optimization strategies, model architectures, and efficiency enhancements to accelerate our scientific breakthroughs.About the PositionWe are on the lookout for a dynamic technical research lead to spearhead our embeddings-focused retrieval initiatives. You will oversee a talented team of research scientists and engineers committed to developing foundational technologies that enable models to access and utilize the right information precisely when needed. This includes crafting innovative embedding training objectives, architecting scalable vector storage, and implementing adaptive indexing techniques.This pivotal role will contribute to various OpenAI products and internal research initiatives, offering opportunities for scientific publication and significant technical influence.This position is located in San Francisco, CA, where we embrace a hybrid work model, requiring three days in the office weekly, and we provide relocation assistance for new hires.Your ResponsibilitiesLead cutting-edge research on embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning.Supervise a team of researchers and engineers in building an end-to-end infrastructure for training, evaluating, and integrating embeddings into advanced models.Drive advancements in dense, sparse, and hybrid representation techniques, metric learning, and retrieval systems.Work collaboratively with Pretraining, Inference, and other Research teams to seamlessly integrate retrieval throughout the model lifecycle.Contribute to OpenAI's ambitious vision of developing AI systems with robust memory and knowledge access capabilities rooted in learned representations.You Will Excel in This Role If You PossessA proven track record of leading high-performance teams of researchers or engineers within ML infrastructure or foundational research.In-depth technical knowledge in representation learning, embedding models, or vector retrieval systems.Familiarity with transformer-based large language models and their interaction with embedding spaces and objectives.Research experience in areas such as contrastive learning and retrieval-augmented generation.

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.

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.

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

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 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 the RoleHex is at the forefront of AI-driven solutions, revolutionizing Data Science and Data Analytics workflows. As an AI Research Engineer at Hex, you will collaborate with product teams to create cutting-edge AI experiences, such as the Notebook Agent. Your role will involve conducting experiments, refining models, deploying AI infrastructure, and developing experimentation tools.Central to our AI experiences is the ability to provide relevant context to the agent. In this role, you will focus on enhancing our search and context architecture, building essential components of our agentic platform, including agentic search and discovery subagents, as well as large-scale, permissions-aware indexing systems.If you are a passionate builder eager to deliver these capabilities to thousands of users, join us on the premier Data Science platform, equipped with exceptional user context.We seek a senior engineer with a background in AI Engineering, Software Engineering, or Machine Learning Engineering, who is keen to broaden our capabilities across several innovative applications. As an early member of our team, you will engage in diverse initiatives, including:Exploring novel agentic techniques for search, discovery, and context managementDesigning and implementing scalable search and indexing architecturesWorking on cutting-edge production AI applications for real customersThis position offers significant opportunities for both personal and professional growth, with numerous technical and leadership prospects based on your interests.Our goal is to provide AI capabilities that significantly enhance and accelerate the data science workflow. We have an exciting roadmap ahead and are eager to share more details during the interview process. We particularly welcome candidates who are enthusiastic about the potential within this field.

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.

About the Foundations Retrieval Team The Foundations Research group at OpenAI explores new approaches that could shape artificial intelligence for years to come. The team focuses on improving the science and data behind model training and scaling, especially for future advanced models. Areas of focus include data utilization, scaling laws, optimization strategies, model architectures, and efficiency improvements. Within Foundations, the Search team builds agentic search solutions. This group works closely with others to design interfaces between models and the core search stack, serving, indexing, and retrieval, so model intent leads to reliable, real-world results. The team develops large-scale systems to transform and index massive information sources, enabling models to reason over global knowledge. Close collaboration with researchers helps move new modeling ideas into production quickly, changing how intelligent systems discover and synthesize information at scale. Role Overview OpenAI is hiring a Software Engineer with expertise in retrieval system development and scalability for its San Francisco office. This role involves working with researchers and engineers to build infrastructure that lets models access the right information when needed. Responsibilities include designing and operating indexing systems, retrieval pipelines, and serving layers. Work in this role will directly improve retrieval capabilities across OpenAI’s research and products, with a strong influence on system performance, reliability, and scalability. What You’ll Do Develop and scale retrieval infrastructure, including indexing, serving, and query execution. Build low-latency, high-throughput systems for real-time model interactions. Work with research teams to bring embedding and retrieval methods into production. Support dense, sparse, and hybrid retrieval pipelines. Maintain system performance, reliability, and observability at scale. Collaborate with Pretraining, Inference, and Product teams to deliver end-to-end retrieval solutions. Help develop model-system interfaces for agentic workflows. Who We’re Looking For Experience building and scaling distributed systems. Background in developing high-performance, low-latency systems. Hands-on work with indexing and retrieval techniques. Familiarity with hybrid retrieval systems. Comfort working collaboratively across multiple teams.

Job DescriptionEmbrace the future of competitive advantage with Eragon, where we create bespoke AI systems that are meticulously tailored to understand your unique business landscape.At Eragon, we focus on developing AI models that leverage proprietary data, deployed directly within customer environments and continuously refined through real-world interactions. Our models not only respond but evolve, improving with each user engagement.We utilize a cutting-edge reinforcement learning framework known as RLQF (Reinforcement Learning from Query Feedback) that transforms user interactions into valuable training signals, establishing a cycle of ongoing enhancement that surpasses traditional fine-tuning methods.The RoleAs an Applied Research Engineer, you will be responsible for designing, training, and deploying advanced models that drive real business operations.This position is not about theoretical research; you will engage directly with customer data, constraints, and feedback, crafting solutions that excel in production settings. You will manage the entire lifecycle of the project, from defining the problem and designing data structures to training, evaluating, and iterating based on live performance.What You’ll DoTrain and adapt models: Fine-tune and post-train models on customer-specific data utilizing RLQF among other techniques.Close the loop: Convert real user interactions, corrections, and workflows into actionable training signals.Own end-to-end systems: Oversee the process from data ingestion and curation through to training, evaluation, and deployment.Evaluate in production: Create evaluation frameworks that accurately reflect real-world performance, rather than relying solely on benchmarks.Work with customers: Collaborate closely with users to comprehend their workflows and translate these into model functionalities.Ship and iterate: Focus on the continuous improvement of models based on live feedback and measurable outcomes.What We’re Looking ForExtensive hands-on experience in training, fine-tuning, or post-training machine learning models.Proficiency in handling messy, real-world data as opposed to only clean benchmarks.Familiarity with reinforcement learning techniques, feedback-driven training such as RLHF or RLAIF, and evaluation systems.Adeptness at quickly transitioning from problem identification to data management, model development, and iterative improvement.Strong engineering instincts with a comfort level in managing systems end-to-end.A proactive approach to shipping and enhancing systems, rather than solely focusing on research.

ABOUT USAt Applied Compute, we are pioneers in developing Specific Intelligence for enterprises, creating agents that learn continuously from a company’s processes, data, expertise, and objectives. Our mission is to establish a continual learning platform that captures context, memory, and decision traces throughout the organization, enabling specialized agents to perform meaningful tasks.Why Join Us: Our team operates at a unique intersection of innovation. Our product team is responsible for crafting a platform that serves as the backbone for a new generation of digital coworkers. Meanwhile, our research team explores the cutting edge of post-training and reinforcement learning to enhance product experiences. Our applied research engineers collaborate closely with clients to deploy agents effectively in real-world scenarios. This synergy of robust product development, extensive research, and direct client engagement is essential for us to revolutionize AI in the enterprise landscape.Our Team: Comprising engineers, researchers, and operations experts, our team includes many former founders with extensive experience. We have developed RL infrastructure at OpenAI, data foundations at Scale AI, and other systems at companies like Two Sigma and Watershed. We proudly serve Fortune 50 clients and are supported by top-tier investors including Kleiner Perkins, Benchmark, Sequoia, Lux, and Greenoaks.Who Thrives Here: We seek individuals passionate about utilizing cutting-edge research and complex systems to address real-world challenges. Comfort navigating diverse environments, whether it’s a new codebase, unfamiliar customer data architecture, or unexplored problem domains, is essential. Our team values genuine client engagement — listening, empathizing, and understanding the realities of work in their organizations. Those with entrepreneurial spirits, rich project experiences, or proven capabilities to manage tasks end-to-end will excel in our environment.THE POSITIONAs a Software Engineer, you will be instrumental in building the products and interfaces utilized by customers and internal teams. You will manage the entire application platform stack, from collaborative human-AI workspace systems to backend workflows orchestrating sandboxed agent sessions, and the continual learning SDK that provides engineers with oversight of the agent development lifecycle.

WHO WE AREAt Applied Compute, we are pioneering the development of Specific Intelligence tailored for enterprises. Our innovative agents continuously learn from a company’s processes, data, expertise, and goals, creating a dynamic learning layer that captures context, memory, and decision traces. This empowers specialized agents to tackle real-world tasks effectively.Why We're Excited: We operate at a unique convergence of technology and practical application. Our product team is responsible for developing the platform that drives a new generation of digital coworkers. Simultaneously, our research team explores the cutting-edge of post-training and reinforcement learning to craft exceptional product experiences. Our applied research engineers work closely with clients to deploy agents into production, ensuring that we combine strong product development with deep research and hands-on implementation.Our Team: We are a diverse group of engineers, researchers, and operators, many of whom are former founders. Our backgrounds include building reinforcement learning infrastructure at OpenAI, data foundations at Scale AI, and operational systems at other leading tech companies. We are proud to collaborate with Fortune 50 customers and are supported by top-tier investors like Kleiner Perkins, Benchmark, Sequoia, Lux, and Greenoaks.Who Thrives Here: We seek individuals who are passionate about applying innovative research and complex systems to solve real-world challenges. Candidates should be adept at quickly navigating unfamiliar environments—be it a new codebase, a client's data architecture, or a novel problem domain. Our team values empathy and understanding in our customer interactions, so those who enjoy listening, learning, and delivering results tend to excel here.THE ROLEAs a Forward Deployed Engineer, you will engage directly with customers to deploy and integrate our platform within their technical environments. You will be responsible for constructing the infrastructure and tools necessary to transform research into production systems. This role requires ownership of customer engagements from start to finish, including architecting environments, building large-scale data pipelines, creating evaluation frameworks for model training, and ensuring our platform delivers scalable value.

About UsAt Applied Compute, we specialize in developing Specific Intelligence tailored for enterprises. Our innovative agents are designed to continuously learn from a company’s processes, data, expertise, and objectives. Currently, there exists a significant disparity between the capabilities of AI models in isolation and their reliable performance within real business environments. These systems often fail to adapt to feedback. We are creating a continual learning layer: a robust platform that captures context, memory, and decision-making traces throughout the enterprise, fostering an environment where specialized agents can effectively perform real work.Why Join Us? We are at a unique crossroads in technology. Our product team is focused on developing the platform that will enable a new generation of digital coworkers. Our research team is at the forefront of advancing post-training and reinforcement learning, leading to groundbreaking product experiences. Our applied research engineers work closely with customers, assisting them in deploying models into production. This blend of strong product focus, deep research, and direct customer engagement is our belief in how to advance AI in the enterprise. We take pride in being product-led, research-enabled, and forward-deployed.Our Culture: Our team is composed of engineers, researchers, and operators, many of whom are former founders. We have developed RL infrastructure at OpenAI, created data foundations at Scale AI, and built systems at Together, Two Sigma, and Watershed. We collaborate with Fortune 50 clients, as well as companies like DoorDash, Mercor, and Cognition. We are fortunate to have backing from leading investors such as Benchmark, Sequoia, and Lux.Ideal Candidates: We are seeking individuals who are passionate about applying innovative research and complex systems to solve real-world challenges. You should feel at ease navigating unfamiliar environments—be it a new codebase, a customer’s data architecture, or an entirely new problem domain. A genuine enjoyment in working with customers—listening, empathizing, and understanding their workflows—is essential. We find that former founders, individuals with numerous side projects, or those who have demonstrated an ability to take ownership of projects from start to finish thrive in our environment.The RoleAs a Product Engineer, you will be instrumental in building the platform that supports a new era of digital coworkers, equipping human knowledge workers with the leverage similar to what coding agents provide developers today. This role is pivotal as you will manage projects from inception to completion within our continual learning platform and work closely with both Applied Research and Research Systems, ultimately helping define a new category of technology. Your work will encompass the entire technology stack, including cloud-hosted sandbox environments and enterprise-grade solutions.

Exa is at the forefront of technology, developing an innovative search engine tailored for AI applications. Our team is dedicated to creating robust infrastructure that enables us to crawl the web, build cutting-edge embedding models for indexing, and develop high-performance vector databases in Rust. We proudly operate a $5M H200 GPU cluster capable of powering tens of thousands of machines.As a Generalist Research Engineer, you will collaborate across our search and retrieval stack, focusing on crawling, parsing, machine learning performance, and retrieval algorithms. Your contributions will directly enhance the quality of search endpoints for our users.

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.