Applied Scientist in New York

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection, error outliers and faulty deployment analysis. As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performa

The Dashboards product is Datadog's unified single-pane-of-glass for metrics, logs, and traces—a comprehensive treasure trove of observability data. We are transforming Dashboards into an AI-native control surface and the central hub where every team moves seamlessly from question to insight to action – providing a guided experience that feels like having an expert SRE at your side and ensuring the entry point is never an empty canvas. We're hiring a Staff Applied Scientist to define and guarantee the quality of this AI system at scale. "Good" isn't one number — it spans answer quality, tool-selection accuracy (critical given the growing catalog of data sources and visualizations), retrieval relevance, latency, token cost, and end-to-end agent success. The space is full of open questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when a user’s query can result in the agent making decisions against dozens of visualizations and data sources – both of which are growing month over month? How do you build a measurement system that catches regressions across all widget types and data sources (e.g., enforcing correct grouping, sorting, and time overrides), and is easy to use and extend by dozens of teams? If those are the problems you want to spend your time on, come build this with us. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the evaluation strategy for Dashboards, as well as sister teams within our organization. Define the metrics — offline and online, quality and cost, single-turn and multi-turn — that the team and the broader organization optimize against. Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, an

Team description At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time. This role is about that last piece. We're hiring a Staff Applied Scientist to define what "good" means for an Agentic interface at Datadog and to build the measurement systems that make it true. "Good" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release. The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do: Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quali

Applied AI is where Datadog's ambitious AI bets get built and shipped ( Bits Chat , updog ). We sit at the intersection of research and product: turning promising capabilities from Datadog AI Research lab and the research community into production systems that reach real customers. The team builds the foundations for agentic systems capable of operating at scale in complex production environments. Current bets span agents that run autonomously at scale, context and memory layers that make those agents more intelligent over time, and tools that help customers build and validate AI-native services in production. The mandate is to move fast from idea to customer impact, and when a product finds its footing, to set it up for growth. As an Engineering Manager I in Applied AI, you will lead a team of engineers and applied scientists working on one of these challenges. You will define technical direction, run short feedback loops, make deliberate decisions about what to pursue or stop, and work closely with product managers, research teams, and cross-functional partners to ship AI capabilities that matter. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Lead and develop a team of engineers and applied scientists focused on building the foundations for agents operating at scale Work closely with product managers, research teams, and cross-functional partners to shape the team's bets from initial framing through to broader adoption, with a clear definition of success criteria at each stage Own end-to-end delivery of high-quality AI systems, from early research exploration to production-grade reliability, with high standards for operational excellence, system reliability, and technical quality Navigate the unique challenges of shipping AI-powered products: balancing quali

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Fraud Data team within Plaid's Fraud organization. We leverage relationships and activity across Plaid’s network to develop machine learning models that help customers detect and prevent fraud while minimizing friction for legitimate users. Our team owns the full model lifecycle, from data processing and experimentation to feature pipelines, model serving, and monitoring. In this research role, you’ll partner closely with Machine Learning Engineers and Data Scientists to uncover new signals, explore and evaluate innovative modeling approaches, and translate promising research into production-ready solutions that strengthen fraud detection across Plaid’s network. As a Senior Research Scientist, you will lead applied research to develop next-generation fraud detection models across relational graphs, sequential events, images, and video data. You’ll design rigorous experiments and evaluation methodologies that reflect real-world fraud dynamics, while exploring state-of-the-art approaches such as Graph Neural Networks and Transformer-based foundation models. In close partnership with Machine Learning Engineers, you’ll translate promising research into production-ready solu

Become a part of our caring community Help shape practical, responsible AI solutions that improve healthcare experiences and outcomes. Humana’s Enterprise AI organization develops safe, scalable AI solutions across our Insurance and CenterWell businesses. We bring together product managers, data scientists, engineers, policy experts, and business leaders to apply emerging technology to meaningful healthcare challenges. As Associate Director of Applied AI, you will lead teams that design, build, and deploy enterprise AI solutions, with a focus on generative AI and intelligent agents. You will connect technical strategy to business needs, guide responsible delivery in a regulated environment, and help teams turn promising ideas into measurable outcomes for members, patients, and associates. Key Responsibilities Lead and mentor teams developing production-ready AI solutions that improve healthcare delivery, member experiences, and business operations. Help define and execute the roadmap for applied AI initiatives in alignment with enterprise priorities and business needs. Guide the evaluation and adoption of machine learning, generative AI, large language models, multimodal models, and intelligent agent technologies. Oversee scalable APIs, frameworks, data pipelines, retrieval-augmented generation solutions, and agent orchestration capabilities. Partner with product, data science, engineering, architecture, security, and business teams to translate requirements into reliable solutions. Establish standards for AI evaluation, obse

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Our Solution Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud. This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions. IN THIS ROLE YOU WILL GET TO: Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas. Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases. Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback. Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos. Influence, tailor and maintain Sales Engineering AI and ML selling assets, inc

About the Team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and startups. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. As an AI Deployment Engineer (ADE) in the OpenAI for Global Affairs team, you’ll help government and non-profit agencies transform their organization through solutions such as automated content generation, contextual search, and novel applications that make use of our newest, most exciting models and technology. About the Role OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe that achieving our goal requires effective engagement with public policy stakeholders and the broader community impacted by AI. The Global Affairs team builds authentic, collaborative relationships with public officials and the broader AI policymaking community to inform and support our shared work in these domains. We ensure that insights from policymakers inform our work and - in collaboration with our colleagues and external stakeholders - help shape policy guardrails, industry standards, and safe and beneficial development of AI tools. We are looking for an AI Deployment Engineer to collaborate directly with our Global Affairs team to help public sector actors unlock the benefits of OpenAI tools and products, aiming to broadly benefit humanity. This includes supporting a workforce organization deploying Certifications programs or advising a government partner on responsible implementation practices. Your role will integrate technical expertise with our mission to ensure that artificial general intelligence benefits all of humanity. In this role, you will: Technical Enablement & Deployment Serve as the primary technical advisor for Global Affairs partnersh

About the Team The AI Architect team partners with organizations to turn OpenAI's most capable models into meaningful, real-world impact. We work with customers across industries and digital-native businesses to identify where AI can create value, design secure and scalable solutions, and help those solutions move from early exploration into sustained production adoption. The team brings together technical strategy, customer partnership, and practical deployment expertise, working closely with Sales, Product, Engineering, Research, and specialist delivery teams. About the Role As an AI Architect, you will be the senior technical owner for a named portfolio of customers and the primary technical counterpart to their leadership teams. You will act as the “CTO of your book of business”, shaping each customer's AI strategy and guiding their journey from pre-sales discovery and solution evaluation through deployment, adoption, and measurable business impact. You will own the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex, and other agentic AI solutions. In partnership with the Account Director, you will translate business priorities into a focused use-case portfolio, an actionable adoption roadmap, and a clear path to durable customer value and growth. The Account Director owns commercial strategy; you own the technical strategy, customer journey, and path to production value. You will remain accountable for the technical outcome while bringing in the right specialists across deployment, implementation, enablement, security, product, and partners to provide deeper expertise and execute work where needed. This role calls for strong industry fluency, sound architectural judgment, and the ability to move confidently between executive strategy and hands-on technical conversations. In this role, you will: Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of existing customers and pre-sales prospect

About the team The Applied AI Engineer, Digital Natives team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of frontier AI use cases for their industry and drive them to production through strong technical guidance. As an Applied AI Engineer in the Digital Native segment, you’ll help large and highly sophisticated companies transform their business through custom AI solutions applications such as customer service, automated content generation, contextual search, personalization, and other novel use cases leveraging OpenAI’s newest, most exciting models and latest capabilities. About the role We are looking for a driven solutions leader with a product mindset to partner with our customers and ensure they achieve tangible business value with frontier AI. You will pair with senior customer leaders to establish AI strategic roadmaps and identify the highest value applications. You’ll then partner with their engineering and product teams to move from prototype through production. You’ll take a holistic view of their needs and design an enterprise architecture using OpenAI APIs and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product. This role is based in our NYC office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Deeply embedded with our most sophisticated and technical platform customers, serving as their technical thought partner in ideating and building novel applications on our APIs. Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. Experiment and prototype solutions with and for your customers. Forge and manage relationships wi

About the Team The Technical Success team helps OpenAI’s customers realize meaningful and sustained value from our technology. We partner with customers throughout their journey—from initial exploration and solution design to production implementation and organization-wide adoption. Applied AI Engineers serve as trusted technical partners to customer executives, engineering teams, product leaders, security organizations, and transformation teams. They combine deep technical judgment with strong customer instincts, translating frontier AI capabilities into secure, reliable systems and durable business outcomes. About the Role We are seeking a Manager to build, lead, and develop a high-performing team of Applied AI Engineers supporting our enterprise customers. You will be accountable for the technical success of a broad and strategically important customer portfolio. You will help your team identify high-value opportunities, design and deploy production-grade AI systems, navigate complex technical and organizational constraints, and expand successful implementations across workflows, teams, and business units. This role requires technical depth, people leadership, customer judgment, and operational rigor. You should be comfortable coaching engineers through architecture and evaluation decisions, engaging directly in high-stakes customer situations, and collaborating with Sales, Solutions Engineering, Product, Research, Engineering, Security, and Legal. You will also help define how we serve enterprise customers at scale by developing effective coverage models, reusable implementation patterns, technical enablement, escalation mechanisms, and systems for turning field insights into high-quality product feedback. In This Role, You Will Build, manage, and develop a high-performing team of Applied AI Engineers supporting large and complex enterprise customers. Own the quality and impact of the team’s work across solution design, implementation, production readiness, adop

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. At Snowflake, we empower both enterprises and individuals to reach their full potential. Our culture prioritizes impact, innovation, and collaboration, making Snowflake the ideal place to build ambitious projects, execute quickly, and advance technology — and your career — to the next level. The Role We are seeking a Manager, Applied Field Engineering - AI/ML Product Specialists to lead a high-performing team of Applied Field Engineers within the Applied Field Engineering organization. In this hands-on leadership role, you will manage a team of Applied Field Engineers who specialize in Generative AI, Machine Learning, and Advanced Analytics. You will be responsible for coaching your team through technical sales engagements, driving execution excellence, and ensuring customers successfully activate and consume Snowflake's AI/ML capabilities. You will translate team-level insights into feedback that shapes broader strategy, working closely with your manager and cross-functional partners to align execution with organizational priorities. Responsibilities & Focus Areas: Technical Execution & Consumption Activation: Drive team performance toward Consumption Activation — ensuring customers successfully move workloads into production and realize contracted credit value Coa

About the Team The Astral team builds high-performance developer tools to power the future of programming, at OpenAI and beyond, including Ruff, uv, and ty. The Astral toolchain sees hundreds of millions of installs per month and powers hundreds of millions of package downloads per day for the Python ecosystem. As a team, we are building on those foundations to continue solving impactful tooling problems as programming evolves. About the Role We are looking for an experienced software engineer to build next-generation programming language tooling. If you like writing high-performance Rust, it could be a good fit; if you like thinking about the future of programming, it could also be a good fit. Strong candidates tend to have deep experience with Rust, Python, open source, compilers, or developer tools — but few candidates are deep in all of these areas, and we've hired candidates without prior Rust or Python experience. In this role, you will: Design and implement features in Astral’s existing open source projects (Ruff, uv, ty, and python-build-standalone, and more). Support Astral’s open source projects as a maintainer, triaging user issues, reviewing pull requests, and participating in community discussions. Evolve the Astral toolchain to accelerate development velocity at OpenAI. Build entirely new tools, in entirely different programming ecosystems, to power the future of agentic software development. Your background might look something like: 5+ years of professional engineering experience, excluding internships, in relevant engineering roles. High agency and comfort operating in a fast-moving environment, with strong ownership of security, reliability, and operational excellence. Strong developer empathy and communication skills, including experience maintaining open source projects. Exceptional systems engineering fundamentals and a track record of leading complex projects from ambiguous problem statements through to user impact. Proficiency in one or more s

You will lead a small, hands-on engineering team building the secure, scalable Core Analytics Data Access Platform that accelerates Datadog’s Applied AI and analytics capabilities. The team owns the Data Access Platform — a unified interface that lets AI and analytics teams discover and self-serve production-ready datasets while abstracting underlying systems and embedding required legal and compliance guardrails. In this role you’ll own technical direction, contribute to design and code, and partner closely with Applied AI, Product Analytics, and internal platform teams to provide reliable datasets and APIs for model training and analysis. This role balances day-to-day engineering leadership with long-term platform planning. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead a Hands-On Engineering Team: Manage, mentor, and grow a small team of 2–4 data engineers (mix of senior and junior) across Paris and NYC, fostering technical excellence and career development. Own Technical Direction and Delivery: Define architecture, engineering priorities, and the team roadmap for the Data Access Platform, driving implementation of scalable, secure data pipelines and platform services. Contribute to Design and Code: Spend substantial time coding, reviewing, and shipping critical platform components to ensure performance, reliability, and operational excellence. Partner with Internal Stakeholders: Work closely with Applied AI, Internal Product Analytics, product managers, and platform teams to define data contracts, APIs, SLAs, observability, and curated analytical datasets. Ensure Data Security, Governance, and Reliability: Implement access controls, lineage, monitoring, and compliance guardrails to support safe model training and repeatable analytics workflows.

Datadog's Software Engineers with Systems depth leverage their experience with systems and tooling to build software that ensures Datadog remains reliable, performant, and secure. For this track, their Software Engineering experience may resemble the Distributed Systems track, but is typically applied in combination with their systems experience to build and run internal platforms and tools that our products are built on. These people typically have deep experience building and managing large cloud infrastructure deployments, or leading reliability efforts for orgs similar to ours, or building release machinery to allow hundreds or thousands of devs to do their jobs without stepping on each others' toes. The systems and tooling where they may have experience depth may include (but not limited to): bazel, build tooling, cassandra, CDN, chef, configuration management, container orchestration, consul, docker, elasticsearch envoy, haproxy, kafka, kubernetes, load balancing, network architecture, postgres, redis, release management, RPC frameworks, service discovery, spinnaker, terraform, zookeeper. Bonus: You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government. #LI-KM5 Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan. Th