Data Collector And Annotator 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 Fullstack Software Engineer on CLEAR’s Healthcare team, you will build and scale secure, interoperable identity and data solutions that connect patients, providers, and partners. You’ll operate at the intersection of modern web platforms, healthcare interoperability standards, and high-assurance identity systems powering frictionless, trusted healthcare experiences nationwide. A brief highlight of our tech stack: Python / React / Typescript AWS cloud What you’ll do: Design and deliver secure, scalable fullstack solutions that integrate with enterprise EHR systems and national health information exchange frameworks Build and maintain healthcare data integrations leveraging FHIR (RESTful APIs/JSON) and HL7 v2 messaging to enable compliant, real-time data exchange Develop identity resolution and patient matching capabilities using identifiers such as MRNs and NPIs to ensure integrity across disparate clinical systems Partner with Engineering, Security, Product, and Health Information Management teams to implement compliant, audit-ready workflows for regulated healthcare processes Collaborate with external vendors (e.g., Epic Technical Services) to troubleshoot integration issues, manage deployments across TST/PRD environments, and ensure production reliability How you’ll measure success: Successful delivery and stability of FHIR/HL7 integrations across healthcare partners Reduction in data integrity issues related to patient matching and identity resolution High system uptime and successful production deployments across tiered

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. We are seeking a technical, data-driven Product Management leader to own CLEAR's Marketing Technology platform. This role is responsible for the systems, data, and measurement capabilities that power member acquisition from first touch through enrollment. You will own CLEAR's MarTech ecosystem, including attribution and tracking, audience data infrastructure, CRM and lifecycle marketing platforms, and the integrations that connect marketing signals to actionable insights. Partnering closely with Marketing, Engineering, and Data teams, you'll ensure CLEAR has the tools and intelligence needed to scale growth across paid, organic, and partner channels. What You'll Do: Own the vision, roadmap, and performance of CLEAR's MarTech ecosystem, including CRM, audience activation, tracking, attribution, and marketing data infrastructure. Build best-in-class measurement capabilities across paid, organic, and partner channels, creating a trusted source of truth for acquisition performance. Partner with Marketing to improve audience targeting, lifecycle messaging, SEO/SEM performance, and channel optimization. Drive strategy for audience segmentation, activation, suppression, and first-party data utilization using platforms such as Snowflake and Hightouch. Own the digital enrollment experience, ensuring it is optimized for conversion, personalization, and growth. Define success metrics, manage vendor relationships, and prioritize investments that maximize marketing effectiveness and ROI. What We're Looking For: 8+ years of Product Management experie

Overview: The Insights product is an offering for Guidepoint's institutional investment and corporate clients, now in its 9 th year, that offers teleconferences, surveys, in-person events, and AI-facilitated data and content. The teleconferences live in an online library portal, which covers a wide of industries/topics that enables our clients to make informed decisions. All content features experts from Guidepoint’s proprietary global network and is conceptualized and hosted by former investment professionals (i.e. hedge fund analysts), sell-side equity research analysts, and industry professionals. This is a hybrid position based out of our New York City office. What you'll do: Monitor a coverage universe of public companies within the global enterprise software sector by tracking earnings releases, investor presentations, SEC filings, sell-side research and industry news. Create and moderate teleconferences on timely topics featuring an expert from Guidepoint’s network with the goal of producing actionable insights for clients. Attend industry conferences to host client panels What you have: Bachelor’s degree or Master’s degree Minimum 10 years of sell-side or buy-side analyst experience Must follow bottoms-up, fundamental approach to investment research focusing on individual companies Has covered the Enterprise Software sector; candidates must be current on company/industry knowledge Ability to work in a fast-paced entrepreneurial environment Outgoing personality with the ability to speak with people at all professional levels Intellectual curiosity and desire to learn Effective time management and organizational skills Demonstrated ability to work both individually and as part of a team What We Offer: The annual salary range for this position is $210,000-$230,000. Additionally, this position is eligible for an annual discretionary bonus based on performance. You will also be eligible for the following benefits: 15 PTO days, 10 lega

Overview: The Insights product is an offering for Guidepoint's institutional investment and corporate clients, now in its 9 th year, that offers teleconferences, surveys, in-person events, and AI-facilitated data and content. The teleconferences live in an online library portal, which covers a wide of industries/topics that enables our clients to make informed decisions. All content features experts from Guidepoint’s proprietary global network and is conceptualized and hosted by former investment professionals (i.e. hedge fund analysts), sell-side equity research analysts, and industry professionals. This is a hybrid position based in our New York City office. What you'll do: Monitor a coverage universe of public companies within the global hardware and semiconductor sector by tracking earnings releases, investor presentations, SEC filings, sell-side research and industry news. Create and moderate teleconferences on timely topics featuring an expert from Guidepoint’s network with the goal of producing actionable insights for clients. Attend industry conferences to host client panels What you have: Bachelor’s degree or Master’s degree Minimum 10 years of sell-side or buy-side analyst experience Must follow bottoms-up, fundamental approach to investment research focusing on individual companies Has covered the Hardware and Semiconductor sector; candidates must be current on company/industry knowledge Ability to work in a fast-paced entrepreneurial environment Outgoing personality with the ability to speak with people at all professional levels Intellectual curiosity and desire to learn Effective time management and organizational skills Demonstrated ability to work both individually and as part of a team What We Offer: The annual salary range for this position is $210,000-$230,000. Additionally, this position is eligible for an annual discretionary bonus based on performance. You will also be eligible for the following benefits: 15

OVERVIEW: The Insights product is an offering for Guidepoint's institutional investment and corporate clients, now in its 9 th year, that offers teleconferences, surveys, in-person events, and AI-facilitated data and content. The teleconferences live in an online library portal, which covers a wide of industries/topics that enables our clients to make informed decisions. All content features experts from Guidepoint’s proprietary global network and is conceptualized and hosted by former investment professionals (i.e. hedge fund analysts), sell-side equity research analysts, and industry professionals. This is a hybrid position based in our New York City office. What you'll do: Build and lead a high-caliber research team: Recruit, develop, and manage a group of analysts producing differentiated, investor-grade insights across the technology, media and telecom (TMT) space, with full ownership over research quality, agenda-setting, and output. Own the research strategy and content roadmap: Define what gets covered and why—shaping expert calls, thematic work, and proprietary content aligned with real-time public equity investor demand Drive business growth and AI-enabled innovation: Partner with commercial and product teams to launch new research offerings, leveraging AI to scale insight generation, enhance workflows, and create differentiated products for institutional investor clients. What you have: Bachelor’s degree or Master’s degree Minimum 10 years of sell-side or buy-side analyst experience Must follow bottoms-up, fundamental approach to investment research focusing on individual companies Has covered all parts of the global TMT sector (Enterprise Software, Hardware & Semis and Consumer Internet); candidates must be current on company/industry knowledge Ability to work in a fast-paced entrepreneurial environment Outgoing personality with the ability to speak with people at all professional levels Intellectual curiosity and desire

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

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 SI partners play a key role in bringing our customers' data-backed ambitions to life by implementing and harnessing the power of the Snowflake AI Data Cloud for cutting edge workloads and use cases. Through our partnerships, we enable companies to empower their employees with the data they need when and how they need it to better engage their customers, optimize their operations, and transform their products. The Partner Development Senior Manager role involves driving and nurturing relationships with our System Integrator (SI) partners. Your primary objective is to strengthen and expand the collaboration between Snowflake and these partners to drive growth. In this role you will be responsible for growing the relationship with IBM in the Americas. The success of these partnerships is demonstrated by driving growth with our joint customers, delivering key Go-To-Market (GTM) programs, establishing critical executive relationships, enabling partners to grow their Snowflake competency, and delivering customer success. Your success depends on your ability to drive compelling business strategies, GTM motions and relationships with IBM. Strong communication, experienced strategic alliance leadership, and problem-solving skills are vital to excel in this role. HERE ARE SOME KE

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

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. About the Team The Embedded Insights team supports Plaid’s mission to build a world-class suite of intelligence products. We identify the best opportunities to use machine learning in Plaid products, prove out those opportunities, and collaborate with cross-functional partners to turn them into real-world production systems. About the Role As a Senior Machine Learning Engineer on Embedded Insights, you will help shape Plaid’s future by building machine learning-powered products and features. You will initially support the Plaid App, working on a 0-to-1 consumer-facing product and helping establish product-market fit for a new business line. You will work closely with product managers, data scientists, engineers, customers, and other machine learning engineers to translate ambiguous opportunities into effective ML systems that create measurable customer value. In supporting the Plaid App, you will: Build machine learning-based features for a 0-to-1 consumer-facing product. Partner with product managers to translate ambiguous business requirements into machine learning problems and influence product strategy and roadmap decisions. Rapidly iterate and experiment to help drive product

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. Snowflake is about empowering enterprises to achieve their full potential and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology and careers to the next level. Position Overview Snowflake Inc. is seeking a dynamic, strategic, and results-oriented Manager, Field Marketing - US Majors Financial Services to lead field marketing strategy and execution across our highest-value US Financial Services enterprise accounts (Banking, Asset Management, Capital Markets, and Insurance). In this dual-impact role, you will balance high-level strategic planning with hands-on execution. You will directly manage a team of two field marketing individual contributors, driving targeted field marketing programs and executive engagements that accelerate adoption of Snowflake’s AI Data Cloud within the financial services sector. Success requires strong cross-functional leadership, deep alignment with Enterprise Sales leadership, and a data-driven approach to pipeline creation, account expansion, and ROI. Key Responsibilities Strategy & Account Planning: Own and execute the end-to-end field marketing strategy for the US Majors Financial Services vertical, tailoring programs to address

The GTM Strategy & Operations Associate will join a global team driving Datadog’s next phase of growth. We’re interdisciplinary thinkers leveraging diverse business backgrounds in management consulting, investment banking, business development, and tech to accelerate Datadog’s global growth. We work directly with Datadog’s most senior leaders to set strategy, improve efficiency across the business, support data-driven decision-making, own complex operations, and more. In this role, you will serve as the strategic partner for our Enterprise segment in the Americas region, identifying opportunities for revenue growth & sales force effectiveness, spearheading strategic initiatives across our go-to-market teams, and driving critical annual planning activities. This role offers the chance to make an immediate and significant impact as we continue to expand our Americas footprint. 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: Support the Enterprise Strategy & Operations team in addressing strategic and operational challenges faced by the Americas Enterprise sales leadership Partner with senior team members to analyze key business areas and surface insights that inform decision-making Support the design and execution of regional programs, including headcount planning, territory design, pipeline reviews, and business performance tracking Collaborate with cross-functional teams including Sales, Channels & Alliances, Marketing, and Customer Success to execute high-impact initiatives that drive growth and improve sales productivity Support sales leadership in executing critical operating rhythms (e.g., QBRs, forecast reviews, leadership updates) Drive day-to-day operational processes, including stakeholder support, KPI management, and process

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 operates on a hybrid schedule requiring two days of in-office collaboration per week. The position must be based out of our New York City office. About The Role Taskrabbit connects busy people in need of help with trusted local Taskers who can lend a hand with everything from home repairs to errands, with the goal of being the number one home services platform in the countries we serve. A Tasker gets paid to do what they love, when and where they want — all while saving the day for someone in their city. The Tasker Operations team helps Taskers achieve their personal tasking goals using Taskrabbit. The Tasker Operations Manager plays a critical role in onboarding Taskers seamlessly, nurturing them, ensuring that they are fully utilized and retained, and building satisfaction with the platform. We’re proactive—helping Taskers before they realize they need support. These approaches, employed at the local level, r

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

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The Chan Zuckerberg Biohub New York is an independent nonprofit research institute that brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine. Biohub itself supports some of the brightest, boldest engineers, data scientists, and biomedical researchers to investigate the fundamental mechanisms underlying disease and develop new technologies that will lead to actionable diagnostics and effective therapies. We are guided by our values of scholarly excellence; disruptive innovation; hands-on engineering/hacking/building; partnership and collaboration; open communication and respect; inclusiveness; and opportunity for all. Our Vision We pursue large scientific challenges that cannot be pursued in conventional environments We enable individual investigators to pursue their riskiest and most innovative ideas The technologies developed at Biohub facilitate research by scientists and clinicians at our home institutions and beyond Diversity of thought, ideas, and persp