Records Retrieval Representative Jobs

Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. Responsibilities Push search and agent quality forward through improvements to models, training data, tools, and system design. Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. Design and build agent harnesses around the tools, context management, execution environments, and orchestration that support reliable work over many steps. Improve retrieval and ranking models and the search interfaces agents use to find and assess information. Build datasets, reward signals, and evaluations that expose meaningful failures and guide improvements. Own experiments end to end, from a clear hypothesis to scalable training, deployment, and measurable gains in quality, latency, and cost. Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring new capabilities into production. Qualifications A strong track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems. Strong software engineering skills and the ability to work across model training, experimentation infrastructure, and production systems. Experience designing rigorous evaluations

Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. Responsibilities Push search and agent quality forward through improvements to models, training data, tools, and system design. Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. Design and build agent harnesses around the tools, context management, execution environments, and orchestration that support reliable work over many steps. Improve retrieval and ranking models and the search interfaces agents use to find and assess information. Build datasets, reward signals, and evaluations that expose meaningful failures and guide improvements. Own experiments end to end, from a clear hypothesis to scalable training, deployment, and measurable gains in quality, latency, and cost. Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring new capabilities into production. Qualifications A strong track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems. Strong software engineering skills and the ability to work across model training, experimentation infrastructure, and production systems. Experience designing rigorous evaluations

GAQ126R40 We're looking for a Product Manager to lead the strategy, implementation, and evolution of our SAP platform. In this role, you'll define the product vision for SAP as the foundation of Finance operations while building the intelligent automation layer that transforms manual, transaction-heavy processes into streamlined, AI-powered workflows. Working closely with Finance and Engineering, you'll shape the future of finance operations by combining the strength of SAP with agentic AI to deliver a simpler, more automated, and more intelligent experience for Finance users. The Opportunity SAP will serve as the foundation for Databricks' core finance processes, including Record-to-Report, Source-to-Pay, and Order-to-Cash. As the SAP Product Manager, you will shape how Finance users interact with these processes by building an intelligent, AI-powered agentic layer on top of SAP. Rather than navigating multiple systems and performing manual tasks, Finance teams will rely on AI-driven workflows that automate routine work, surface the right insights, and guide users through exceptions and approvals. Your mission is to combine the strength of SAP with the power of the Databricks AI to create a modern, highly automated finance experience that enables the business to scale. The impact you will have: Own the SAP & Intelligent Automation Strategy: Lead the product strategy and roadmap for Databricks' SAP platform, ensuring it serves as the foundation for scalable, best-in-class finance operations. Drive SAP implementations, platform evolution, and business process transformation while defining the automation roadmap that leverages AI and agentic workflows to simplify user experiences, reduce manual effort, and improve operational efficiency. Lead the AI & Agentic Layer: Design, build, and deploy intelligent agentic workflows on top of SAP, partnering with engineering and data teams on the orchestration, retrieval, and guardrail patterns that make agents safe

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the role Notion's Search & Context Platform is the substrate that powers how 100M+ users and, increasingly, Notion's agents find and reason over the right information. This team owns the search infrastructure and indexing systems powering lexical and semantic retrieval, the platform primitives for managing agent context and memories , and the scalability, performance, security, and enterprise capabilities that make all of it production-grade. Data growth is faster than ever, and the systems that power this need to rapidly evolve to support an order of magnitude growth—both in the volume of content we index and in the load that agents now place on the retrieval layer. As the Engineering Manager for this team, you'll lead a technically deep group of engineers building platform systems used by multiple product teams. Your most important customers are the Search & Context product team and the AI team (building agents on top of these primitives). You'll set the technical direction, product manage the platform scope on behalf of those customers, and make hard tradeoffs to move fast in service of product velocity — while keepi

Perplexity is seeking an experienced Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. Responsibilities Relentlessly push search quality forward—through models, data, tools, or any other leverage available Architect and build core components of our search platform and model stack Train and evaluate retrieval, ranking and classification models, including LLMs Deploy models - from boosting to LLMs - in a scalable and performant way Build and optimize RAG pipelines for grounding and answer generation Collaborate with Data, AI, Infrastructure and Product teams to ensure fast and high quality delivery Qualifications Deep understanding of search and retrieval systems, including quality evaluation principles and metrics Proven track record with large-scale search or recommender systems Self-driven, with a strong sense of ownership and execution Minimum of 5 years of working on search or recsys-related projects

POSITION SUMMARY Natera is seeking a Principal AI Engineer to set technical direction for, and hands-on build of, the Vector Store GenAI Platform that powers document intelligence and retrieval across our Real-World Data (RWD) organization. The platform ingests clinical documents from multiple sources, indexes them for high-quality search, and makes that content available to downstream AI workflows and business use cases across oncology and other clinical domains. This is a principal-level individual contributor role with architecture-plus-build ownership of retrieval, document processing, and ingestion systems. You will define platform strategy and sequencing, ship production code in a cloud environment, raise the reliability and quality of search and retrieval, and prove new approaches through POCs and benchmarks. You will partner with clinical, engineering, and product leaders to turn ambiguous priorities into a clear technical roadmap, establish standards for how retrieval serves agents and re-extraction workflows, and deliver measurable improvements in platform quality and operability—with high autonomy and limited day-to-day direction. The ideal candidate combines deep hands-on engineering with a track record of owning complex AI platforms end to end. You set direction, implement critical path yourself, and elevate the technical bar across the teams that consume and extend the platform. RESPONSIBILITIES Own platform architecture and hands-on delivery for the Vector Store GenAI Platform, including search and retrieval, document processing and chunking, ingestion pipelines, and APIs that serve downstream AI workflows. Set technical direction for hybrid search and retrieval quality; evaluate embedding models and retrieval approaches through working implementations, POCs, and benchmarks, and drive adoption of what works in production. Advance document parsing and chunking so clinical content is indexed in a way that supports accurate, structured, and faceted retri

About Voyage AI Team at MongoDB Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Position Overview We are seeking a Staff Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. This role can be based out of our Palo Alto office, or remotely in the United States. Responsibilities Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers Innovate in next-generation information retrieval and LLM agent paradigm Collaborate closely with other research scientists and research engineers as well as peers across the organization Qualifications PhD degree in Computer Science or related field A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues Strong background in machine learning, deep learning, and natural language processing Experience building complex neural networks for language and visual understanding Capable of conducting rigorous empirical studies to validate theoretical results Excellent leadership, problem-solving, and communication ski

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. This is NOT a new grad role! This role is for candidates with 0-2 YOE and can start full time right away. About the Role As an engineer at Notion, you’ll help shape core user experiences and accelerate how people discover value in Notion. You'll tackle meaningful challenges with increasing autonomy, crafting code that millions of users will experience. You'll take ownership of projects that matter, make critical technical decisions, and contribute your unique perspective to our product vision. Working alongside passionate experts across design, product, and data, you'll help shape the future of how people work. We're looking for an Early Career AI Engineer to join as a strategic partner in shaping Notion's AI vision. You'll work on cutting-edge AI-powered features, leveraging LLMs, embeddings, and other AI technologies to make Notion more intelligent and capable. This role may be aligned to one of multiple AI-focused teams at Notion. Depending on team match and business needs, you could work on: AI product engineering: building model-powered features end-to-end (UX, APIs, retrieval, orchestration, quality, and reliability) Model &amp

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: Notion is looking for an experienced engineer who has designed and built secure software systems to help define the security foundations for our AI products. You’ll work with product and engineering teams on agent runtimes, tool permissions, retrieval, content writes, observability, and abuse-resistant design. You’ll turn product risks into clear architecture, reusable guardrails, automated tests, and production systems that help teams ship new features safely. This role is based in San Francisco. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Define and build security architecture for product surfaces that operate across customer workspace content, including tool execution, content writes, retrieval, permission checks, provenance, and auditability. Make the secure path the easy path for product teams by shipping reusable libraries, review patterns, test fixtures, and guardrails that prevent classes of vulnerabilities.

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: Notion is looking for an experienced engineer who has designed and built secure software systems to help define the security foundations for our AI products. You’ll work with product and engineering teams on agent runtimes, tool permissions, retrieval, content writes, observability, and abuse-resistant design. You’ll turn product risks into clear architecture, reusable guardrails, automated tests, and production systems that help teams ship new features safely. This role is based in San Francisco. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Define and build security architecture for product surfaces that operate across customer workspace content, including tool execution, content writes, retrieval, permission checks, provenance, and auditability. Make the secure path the easy path for product teams by shipping reusable libraries, review patterns, test fixtures, and guardrails that prevent classes of vulnerabilities.

Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you’ll be part of a passionate team dedicated to accomplishing hard things, together. Principal Applied AI Engineer Location: Remote (US) Lead the engineering of software that matters — driving AI automation for the world's largest enterprises. ABOUT THE TEAM Appian Engineering spans the full depth of our platform: from the foundational layers that power enterprise scale, to the AI capabilities redefining what automation can do. We operate in a highly collaborative, fast-paced environment focused on technical precision, continuous learning, and high code quality. By joining our team, you will solve real-world problems that directly shape how Appian delivers our AI-Powered Process Automation platform to enterprises around the world. THE OPPORTUNITY As a Principal Applied AI Engineer, you will serve as the technical linchpin for applied AI on the team, bringing deep hands-on expertise in designing and operating production LLM systems and a track record of influencing engineering direction beyond your immediate scope. Equipped with cutting-edge AI tooling, you will drive the design and delivery of high-complexity AI systems — spanning code generation, agents, retrieval, structured generation, tool use, model routing, evaluation, and observability — set the technical bar for the team, and lead other engineers towards solutions of real complexity to ensure flawless Enterprise-Grade Orchestration. WHAT YOU'LL DO Develop Clean Software: Architect, build, and optimize high-performance production LLM systems while maintaining a strong personal technical presence on the team. Lead Platform Modernization: Spearhead strategic technological chan

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. We are seeking a highly skilled AI Software Engineer to participate in the development of enterprise-grade AI and Generative AI solutions. This role blends deep software engineering expertise with cutting-edge AI/Generative/Agentic capabilities, focusing on building scalable, secure, and high-performance systems that leverage LLMs, agentic workflows, and retrieval-augmented generation (RAG). You will collaborate across engineering, data science, and product teams to deliver innovative solutions that transform business operations and customer experiences. If you thrive in fast-paced environments, are passionate about AI, and have a track record of delivering impactful software, we want to hear from you. What’s on Offer at D&B Ireland 25 days annual leave (plus 2 paid volunteer days & 1 paid un-sick day) Holiday buy & sell (the option to buy or sell up to 5 additional days per year) Flexible working - hybrid model Employee Health Insurance Mental Health Support program Pension Contribution Family Friendly Leave (Maternity, Paternity, Parental, Marriage and Bereavement) Life Assurance Educational Assistance Program Life-Style Account (D&B will match your contributions up to €40 per month and can be used to claim for a range of health-related, leisure or lifestyle activities) At Dun & Bradstreet, we are 6,000 friendly co

About the Role We're looking for a Senior AI Engineer to help advance Amplitude's AI products and the foundations they're built on. As AI reshapes how customers analyze data, build products, and act on insights, we need engineers who can move fluidly between deep technical work and product judgment, shipping AI capabilities that customers and internal teams actually rely on. This role is both visionary and hands-on. You'll identify where AI creates the most leverage, build the systems that deliver it, and establish the patterns that let the rest of the company build faster on top of your work. You'll contribute to customer-facing AI products, the platform infrastructure beneath them, and the internal tooling that helps Amplitude operate as an AI-native company. What You'll Do Ship high-impact AI features and products that change how customers and internal teams work, from agentic workflows to embedded intelligence across the Amplitude platform Design and build the foundational infrastructure behind Amplitude's AI systems: orchestration, evaluation, retrieval, context management, and integrations with the broader product ecosystem Identify high-leverage opportunities by deeply understanding user workflows, customer pain points, and emerging capabilities in the AI ecosystem Establish reusable patterns, primitives, and components that enable other engineers to build AI features confidently and consistently Drive adoption and quality through close collaboration with product, design, and customer-facing teams, with a relentless focus on real usage and measurable outcomes Set technical direction for AI systems at Amplitude, making thoughtful build vs. buy calls, shaping evaluation strategy, and influencing the long-term roadmap Who You Are You're a highly capable engineer with a strong track record of shipping AI-powered systems that people actually use. You bring deep technical instincts, strong product sense, and a forward-thinking view of where AI is heading. Experienc

Overview We are seeking a hands-on Director of AI Software Engineering to lead and scale AI engineering efforts supporting multiple business units across Governance, Risk, and Compliance (GRC). This role sits at the intersection of product delivery, platform evolution, and applied AI—driving real-world impact across core workflows. This is not a pure management role. We are looking for a builder who leads from the front, someone who has recently written production code, shipped systems end-to-end, and can operate comfortably in ambiguity while aligning teams and stakeholders. What You’ll Do Lead AI Engineering Across GRC Own delivery of AI-powered capabilities embedded directly into business unit workflows (e.g., risk analysis, compliance automation, reporting, due diligence) Partner with product, data, and platform teams to translate business problems into scalable AI systems Stay Hands-On Contribute to architecture, code reviews, and critical path implementation Prototype and validate new approaches (LLMs, agents, retrieval systems, classification pipelines, etc.) Set engineering standards for performance, reliability, and cost efficiency Build and Scale Teams Lead and mentor a high-performing team of AI/ML and software engineers Drive hiring, coaching, and career development Establish a culture of ownership, speed, and technical excellence Drive Execution Deliver production-grade systems—not experiments Balance speed with rigor (security, privacy, compliance) Operate across multiple concurrent initiatives with clear prioritization Communicate and Influence Act as a bridge between engineering and business stakeholders Clearly articulate trade-offs, risks, and outcomes to senior leadership Align cross-functional teams around shared goals and timelines What We’re Looking For Proven Builder 10+ years in software engineering, with recent hands-on coding experience Demonstrated track record of shipping production systems at scale Experience with modern

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. With Roblox’s daily active users growing at a record pace, we are seeking experienced machine learning researchers who thrive on solving complex challenges and designing scalable, ground breaking solutions. In this role, you will innovate on LLMs, VLMs, autoregressive models, or other large models for user understanding, content understanding, recommendation, and agentic search. Your work will lay the foundation for personalizing user experiences, enhancing engagement and retention, and driving growth within the creator ecosystem. In search and discovery, you will contribute to the core systems that enable users to discover and interact with experiences across Roblox. On Search, that work spans the end-to-end user search journey, covering query suggestions, autocomplete, and retrieval and ranking. These systems drive exploration and engagement across all surfaces, helping users find relevant and exciting content. Looking ahead, our team aims to innovate further by developing auto-generated summaries, images, and videos from experience content to improve discoverability and inspire user exploration. Our mission is to connect a billion users with the best content and connections at the right