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Experience Level
Experience
Qualifications
Key Responsibilities
Collaborate with Scale’s Operations team and enterprise clients to convert ambiguity into structured evaluation data, facilitating the development and upkeep of gold-standard human-rated datasets and expert rubrics that form the basis of AI evaluation systems.
Examine feedback and gathered data to discover patterns, enhance evaluation frameworks, and establish iterative improvement cycles that elevate the quality and relevance of human-curated assessments.
Design, research, and develop LLM-as-a-Judge autorater frameworks and AI-assisted evaluation systems, including models that critique, grade, and elucidate agent outputs (e.g., RLAIF, model-judging-model configurations), along with scalable evaluation pipelines and diagnostic tools.
Engage in research projects that investigate new methodologies for the automatic analysis, evaluation, and enhancement of enterprise agent behavior, striving to advance how AI systems are assessed and optimized in practical applications.
Basic Qualifications
Bachelor’s degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
Over 2 years of experience in Machine Learning or Applied Research, with a focus on applied ML systems or evaluation infrastructure.
Hands-on experience with Large Language Models (LLMs) and Generative AI in professional or research settings.
Strong comprehension of cutting-edge model evaluation methodologies and the current research landscape.
Proficiency in Python and major ML frameworks (e.g., PyTorch, TensorFlow).
Solid engineering...
About the job
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.
About Scale AI
Scale AI is at the forefront of AI-driven solutions, dedicated to streamlining operations and enhancing business intelligence through innovative technologies. With a commitment to excellence, we aim to empower enterprises with robust evaluation systems and insights that drive informed decision-making.
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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.
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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.
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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.
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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.
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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
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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.
Nov 13, 2025
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