Model Designer in New York

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. As a Senior Software Engineer, Data, you will design, build, and operate the next generation of our data platform and products – going beyond ID to power a networked digital identity – while keeping member privacy, security, and reliability at the core. What you’ll do: Build and operate scalable, reliable data systems and pipelines – from ingestion to modeling to visualization – so Analysts and Engineers can self-service changes in an automated, tested, secure, and high-quality manner. Develop and maintain end-to-end data products and pipelines (batch and/or streaming) that collect, clean, transform, and model data, and own the infrastructure that powers them to unlock new business use cases and reporting. Implement and maintain infrastructure-as-code, CI/CD, and shared developer tooling for data products (e.g., Pulumi/Terraform, GitHub, orchestration tools like Dagster/Airflow) to make it easy and safe for teams to build, test, and ship changes across environments. Improve the security, compliance, and cost posture of the data stack through robust dependency management, IAM and secrets hardening, observability, and performance/cost optimizations. Partner with product and other stakeholders to uncover requirements, make architectural decisions, and continuously improve our data platform and processes. How you’ll measure success: Data reliability & SLAs: % successful pipeline runs, adherence to freshness SLAs for core datasets, and reduction in data-related incidents impacting stakeholders. Platform quality & efficiency: Reductio

WHAT IS BOX? Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia. By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift. WHY BOX NEEDS YOU Box is expanding into a new era of monetization, one that blends our trusted subscription model with dynamic, consumption-based pricing for AI-powered and Platform capabilities. As the Program Manager, Consumption Products, you will own the day-to-day operations of this early-stage but high-priority business, sitting at the intersection of product, finance, analytics, and our customer-facing teams. This is a rare opportunity to build something new at scale: you will help define how Box monetizes AI Units today and lay the operational foundation for expanding consumption-based models across our Platform and beyond. This role reports to the VP, Renewals and Consumption and carries direct visibility with Box's Chief Operating Officer and othe

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role is hybrid requiring 2 days in office at our San Francisco or NYC hub every Tuesday & Wednesday. About the Role Machine Learning is a cornerstone at Taskrabbit, and we're looking for a Staff Machine Learning Engineer to join our team and lead the next phase of our customer retention strategy. This is a critical, full-stack role for an individual who is passionate about the end-to-end lifecycle: from initial research and model development to building the robust systems that power repeat customer engagement and lifetime value growth at scale. Taskrabbit's greatest growth opportunity lies in deepening customer relationships and accelerating repeat purchases. Our most valuable customers are those who return frequently, discover new service categories, and increase their spending over time. There's significant untapped potential in the marketplace: repeat customers spend 3-5x more than one-time users, and category expan

Datadog is seeking an experienced Legal Operations Manager to join our Legal Operations subgroup. In this role you’ll partner with stakeholders across the organization to scale, modernize, and continue to automate how our global legal team operates including driving the adoption of AI-powered tools and workflows. The Legal team supports Datadog’s rapid growth by providing a wide range of legal services across a highly dynamic technology company, from driving new business via contracts and compliance efforts, to protecting Datadog’s intellectual property. Datadog’s Legal team collaborates with virtually every team across the organization, from engineering to product to marketing. 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 and continuously improve legal processes end-to-end, partnering with legal and non-legal process owners to drive improvements, optimization, and automation Liaise with technical and cross-functional teams to implement solutions, integrate systems, and troubleshoot issues reported by the legal team Create and manage SOPs and collaborate with legal and non-legal colleagues on cross-functional projects Analyze and use data, including AI-generated insights and dashboards, to drive initiatives, support forecasting and planning, and deliver reporting to legal leadership and other stakeholders Manage technology used by the legal team (current tools include Brightflag, Salesforce, ChatGPT, Claude, Perplexity) and become a superuser of new tools Champion new systems and emerging AI capabilities Support the legal team’s outside counsel operations Continuously cross-train across to operate as a flexible member of a shared services model, enabling coverage, resource-sharing, and consistent process standards Who You Are: An expe

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role is hybrid requiring 2 days in office at our San Francisco or NYC hub every Tuesday & Wednesday. About the Role Machine Learning is a cornerstone at Taskrabbit, and we're looking for a Staff Machine Learning Engineer to join our team and lead the next phase of our customer retention strategy. This is a critical, full-stack role for an individual who is passionate about the end-to-end lifecycle: from initial research and model development to building the robust systems that power repeat customer engagement and lifetime value growth at scale. Taskrabbit's greatest growth opportunity lies in deepening customer relationships and accelerating repeat purchases. Our most valuable customers are those who return frequently, discover new service categories, and increase their spending over time. There's significant untapped potential in the marketplace: repeat customers spend 3-5x more than one-time users, and category expan

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

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 Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners. As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features. Responsibilities: Work at the intersection of product analytics, machine learning, and fraud a

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. The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Driver, Marketplace, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing petabyte-scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the Marketplace at Lyft, is responsible for determining what inventory can be reliably offered for a given rider session and fulfilling rider requests. The group comprises several sub-teams that generate feasible offers for riders, match rider requests with drivers, and maintain a distributed state machine to track rides and drivers from request through completion. We are seeking a Machine Learning Engineer to join the Fulfillment team and lead the design, development, and deployment of state-of-the-art machine learning systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging machine learning and data science. Responsibilities: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The tvScientific by Pinterest team is building a new enterprise cross-sell motion focused on growing off-platform revenue in close partnership with Pinterest’s NAMER Enterprise sales team. As a Senior Client Partner, you’ll help establish how we go to market together across CTV, video and programmatic opportunities, creating a seamless experience for customers with integrated needs. You’ll play a key role in shaping the team’s operating model, strengthening collaboration across sales teams and driving incremental revenue across enterprise accounts. What you’ll do: Lead enterprise cross-sell efforts for tvScientific by Pinterest in partnership with Pinterest’s NAMER Enterprise sales team, with a focus on growing off-platform revenue across CTV, video and programmatic opportunities Build and execute joint account plans with Enterprise Client

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is building a centralized Pricing, Yield & Compensation function to bring rigor and visibility to how we price inventory, manage programmatic performance, and compensate our Ads and Lyft Business sellers. This is a high-visibility, cross-functional role sitting within the MBA StratOps function and touching Finance, Analytics, Sales, and Accounting daily. The Manager, Pricing, Yield & Sales Compensation will own three interconnected functions: setting and managing CPM floors, rate cards, and margin targets for our direct-sold advertising inventory; overseeing the performance and economics of our Audience Extension managed service; and partnering with Analytics and Accounting to design, calculate, and administer commissions and compensation for sellers across Lyft Ads and Lyft Business. This role requires an operator who is equally comfortable pulling margin reports, running a compensation calculation model, and holding a vendor accountable to a floor price. Responsibilities: Direct Inventory Pricing & Yield Management: Own the Lyft Ads rate card strategy across all direct-sold formats (display, in-app, sponsored placements) and enforce pricing discipline through the order management system, Boostr. Set and manage CPM floors and pricing tiers, and partner with Sales and Ad Ops to evaluate custom deal structures and non-standard pricing requests against margin thresholds. Monitor sellthrough, utilization, and margin by product line, and surface risks and opportunities in weekly and monthly yield reviews. Managed Service Performance Oversight: Serve as the internal owner of our vendor led Audience Extension managed service performance, holding the vendor accountable to agreed CPM targets, margin commitments, and delivery standards. Conduct regular performance reviews of Vendor campaigns,

About Datalab Datalab trains models that read documents reliably at scale. The world’s most important information is trapped in PDFs, scans, and files that can’t easily be parsed, and getting it out correctly matters. From frontier AI labs like Anthropic to Fortune 500s like Siemens, Datalab is where businesses turn when extraction has to be right. We hit an 8-figure run rate with a team of 7. We have hundreds of customers across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools - chandra, surya, marker, and lift - have 70,000+ GitHub stars, millions of monthly downloads, and broad developer mindshare. We’re backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview Marketing at Datalab already has real infrastructure behind it. We run a combined launch and content calendar with a defined playbook - channels, owners, and cadence for every release - and we ship two to three launches a week against it. No one here works on marketing full-time, so nobody owns the larger question of how we show up when a developer, a buyer, or an AI agent goes looking for a document parser. You’d be our first dedicated marketing hire. You’d inherit a working system rather than a blank page, and the job is to make it run reliably, then make it considerably more ambitious. The natural place to build from is our open source work, which reaches a wide audience and currently does less for us than it could. This is a hands-on role. On a team of 7, you’ll write the blog post, draft the tweets, restructure the docs page, brief the agency if we hire one, and pull the numbers yourself. We’re looking for someone who has done this work somewhere it was done well, and who wants to keep doing it rather than direct someone else who does. There is strong potential for this to grow into a leadership role as we hire more people into the marketing team. An increasing share of our buyers never touch a search results page; they ask a model. We want someone who t

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

About the Team The Commercial Sales team helps growing businesses adopt OpenAI’s products and translate emerging AI capabilities into meaningful business outcomes. We work with customers across industries and use cases, helping them evaluate, deploy, and expand their use of ChatGPT and the OpenAI API. Our team partners closely with Growth, Product, Finance, Legal, Revenue Operations, and other cross-functional teams to create a high-quality customer experience and build a scalable commercial sales motion. About the Role We are looking for an Account Director to own customer relationships and the commercial process across the SMB segment, from initial discovery through close and expansion. This is a fast-moving, high-ownership role that combines consultative selling, technical curiosity, and disciplined execution. You will build and manage pipeline, help customers connect their business priorities to OpenAI’s products, and navigate technical, commercial, and executive stakeholders throughout the buying process. You will also play an important role in shaping how OpenAI serves commercial customers by sharing market insights, improving our sales motion, and helping the team build repeatable approaches that support responsible and successful adoption. This role is based in New York NY. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Occasional travel will be required. In this role, you will: Own commercial opportunities from qualification through close, onboarding, and expansion. Build and manage a healthy pipeline across inbound, outbound, and existing customer opportunities. Lead thoughtful discovery conversations and translate customer priorities into compelling use cases for ChatGPT and the OpenAI API. Develop trusted relationships with business, technical, and executive stakeholders throughout the customer organization. Navigate complex commercial processes in partnership with internal teams, including P

Datadog is hiring a Head of Global Executive Support to lead and scale our Executive Support organization. This is a leadership role responsible for the strategy, operations, and people development of a global team spanning Executive Assistants, Senior EAs, Team Leads, and Managers. The leader will serve as the connective tissue between executive leadership and the broader organization, helping to set the standard for operational excellence, building scalable systems, and developing the next generation of EA talent. Datadog's Executive Support team is a high-visibility, high-impact function that directly enables our most senior leaders to operate at their best. As the leader, you'll shape how the entire function runs; building a team culture grounded in excellence, discretion, and genuine partnership. The right person for this role brings deep expertise in executive-level support, a systems mindset, and a track record of leading high-performing administrative organizations. 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 and develop a global, multi-level executive assistant team Define the long-term vision and operating model for Executive Support at Datadog Drive headcount planning, resource allocation, and org design as the company scales Develop and maintain policies, playbooks, and documentation that standardize high-quality support across all executive stakeholders Identify and implement process improvements that increase efficiency and reduce friction across the organization Act as an escalation point for complex, high-stakes, or sensitive executive support needs Maintain discretion and judgment around confidential information at the highest levels of the organization Partner with Finance, Legal, People, and leaders across