Data Collector And Annotator in United States

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 . As the Lead Product Analyst- Lifecycle Marketing, you will serve as the strategic analytics partner for lifecycle and CRM initiatives, helping shape retention strategy through cohort-based insights, experimentation, and cross-functional partnership. You will partner deeply with PMM, Product, and Data Science to measure impact, improve lifecycle programs, and identify the highest-leverage opportunities to drive retention. This role is ideal for someone who combines strong analytical rigor, operational execution, and excellent communication skills. You should be comfortable moving from hands-on analysis to clear recommendations, and from detailed experiment readouts to polished presentations for cross-functional and leadership audiences. What you’ll do Be the analytical thought partner for lifecycle, CRM, and retention strategy. Partn

About the Team GTM Growth Engineering builds AI-native products that help OpenAI's go-to-market and B2B marketing organizations scale with greater speed, intelligence, and operational effectiveness. We apply OpenAI models to real business workflows and build the systems that make those applications useful and dependable: customer context, agent behavior, feedback, evaluation, experimentation, and appropriate human oversight. Our work brings together software engineering, applied AI, product, data, and GTM operations. We measure success through the quality of customer engagement, pipeline, conversion, and the effectiveness of our sales and marketing teams. About the Role We're looking for an Applied AI Engineer to build production systems that help AI-powered go-to-market workflows improve over time. You will connect agent behavior, customer and operator feedback, evaluation, experimentation, and business outcomes to make these systems more effective, reliable, and responsive to evolving customer needs. This is a deeply technical, cross-functional role with end-to-end ownership of the agent improvement loop: understand production behavior, identify failure modes, improve how the system decides or acts, and validate the resulting impact. You will partner with Engineering, Product, Data Science, Sales, and B2B Marketing to turn real-world signals into safer, more effective agent behavior and measurable improvements in customer engagement, conversion, qualified pipeline, and team productivity. In this role, you will: Own the production improvement loop across agent behavior, customer and operator feedback, evaluation, experimentation, and verified business outcomes. Instrument agent workflows so model interactions, tool use, decisions, failures, human edits, and downstream outcomes can be understood in context. Define meaningful quality standards, representative evaluation datasets, regression coverage, and production monitoring for real GTM workflows. Investigate why a

About the Team OpenAI builds powerful AI systems like ChatGPT, the OpenAI API, and enterprise products that serve millions of users across the globe. As we scale, securing our infrastructure, protecting sensitive data, and meeting global compliance standards are essential to our success and societal impact. Security at OpenAI is a cross-cutting function that spans infrastructure, applied engineering, legal, policy, and product. Technical Program Managers (TPMs) play a critical leadership role in aligning teams and delivering execution at scale and this role will be foundational in shaping how we secure OpenAI’s systems, users, and commitments. About the Role We’re seeking a Senior Technical Program Manager to drive cross-functional security, privacy, IT and compliance initiatives at the intersection of infrastructure, product, and policy. You will execute complex programs that reduce internal data access, prevent misuse, and ship security capabilities. You will focus your efforts on the most critical initiatives within Security, crossing the spectrum of insider threat, information security, physical security, and information technology challenges. This role is deeply technical and execution-focused. It requires a structured operator who thrives in ambiguity, partners effectively across boundaries, and applies principled judgment to scale trust, governance, and security across OpenAI’s systems and products. In this role, you will: Drive execution of critical security and compliance programs such as vulnerability management, merger and acquisition security and integration, infrastructure hardening, and datacenter security management. You will need to deeply collaborate on technical architecture and resolve technical problems in partnership with engineering. Partner with IT, Infrastructure, Application, Legal, Privacy, and Security teams to build scalable programs, and deliver critical security outcomes across multiple disciplines, including insider threat, information

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

About the Team OpenAI is helping build the infrastructure that powers the next generation of artificial intelligence. Through Stargate, we are developing and operating large-scale AI compute campuses that require world-class execution across data center design, construction, commissioning, and operations. The Infrastructure Operations team is responsible for bringing AI infrastructure online and ensuring it operates reliably at scale. We partner closely with hardware, network, deployment, construction, and operations teams to deliver mission-critical environments capable of supporting frontier AI workloads. As our footprint expands, operational excellence becomes increasingly important to ensuring safe, reliable, and efficient campus operations. About the Role We are seeking a Facilities Operations Manager to support the commissioning, operational readiness, and long-term operation of next-generation AI data center campuses. This role sits at the intersection of construction, commissioning, hardware deployment, and facilities operations. You will be responsible for ensuring mission-critical infrastructure is prepared to support hardware deployment, transitioned successfully into production operations, and maintained to the highest standards of reliability and availability. You will lead day-to-day operational execution across electrical, mechanical, controls, and supporting infrastructure systems while partnering closely with commissioning teams, site operators, vendors, and engineering organizations. This role requires a strong blend of technical depth, operational leadership, and cross-functional execution. Key Responsibilities Lead day-to-day operations of mission-critical facility infrastructure across AI compute campuses. Own operational readiness activities supporting new campus deployments and infrastructure expansion. Partner with commissioning teams to transition facilities from construction and startup into steady-state operations. Develop, implement, and

About the Team The Privacy Engineering team builds the systems and technical foundations that govern how user data is understood, retained, accessed, and used across OpenAI. We partner with Product, Data, Infrastructure, Security, and Legal to translate policy and trust commitments into durable architecture and enforceable controls. Our work spans data inventory and mapping, classification and lineage, retention and deletion, access governance, purpose and usage controls, auditability, and lifecycle automation. We aim to make policy-aligned data handling the default while giving teams clear, reliable primitives for building and operating products at scale. About the Role We are looking for an experienced Software Engineer to drive the architecture and execution of user data governance across OpenAI. You will define technical direction, build shared platforms and controls, and lead cross-functional programs that make data flows discoverable, policies enforceable, and ownership explicit. This role is well suited to a senior engineer who can move between deep systems design and organization-wide influence, turn ambiguous requirements into pragmatic roadmaps, and operate high-trust systems end to end. This position is based in San Francisco. Relocation assistance is available. In this role, you will: Set the technical strategy and architecture for user data governance across data mapping, classification, lineage, retention, deletion, access, and permitted usage. Design and build shared services, APIs, metadata systems, and policy-enforcement mechanisms that make governance controls consistent, scalable, and auditable. Establish reliable inventories of user data, system ownership, data flows, and policy applicability across products, infrastructure, analytics, and research systems. Partner with Product, Data, Infrastructure, Security, and Legal leaders to define decision rights, translate requirements into controls, and drive adoption across teams. Own governance systems

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. Learn more about OpenAI’s approach to safety About the Role As an Analytics Engineer in Safety Systems, you will play a pivotal role in building a data-centric culture, enhancing decision-making processes, and driving strategic initiatives through analytics. You will partner closely with Engineering, Research, and Data Science to develop and maintain canonical data sources and source-of-truth dashboards that enable both people and AI agents across the organization to derive trustworthy, actionable insights. You will own the consumption layer for safety metrics: defining intuitive, reliable ways for stakeholders across Safety Systems, partner teams, and leadership to understand the safety of our products, answer safety-related questions independently, and inform product decisions and company strategy. Most importantly, you will be a core member of the Safety Systems team, collaborating with researchers and engineers to advance our goals of safe, robust, and reliable AI. This role is based in San Francisco, CA. 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: Design and maintain canonical datasets that serve as sources of truth for safety metrics. Develop and refine data products such as dashboards, reports, agent-enabled workflows, and machine-readable interfaces that empower stakeholders to extract and analyze data independently. Work closely with stakeholders in Engineering, Research, and Data Science to understand their decision-making n

About the Team OpenAI’s Industrial Compute team is responsible for building and scaling large-scale compute capacity across first-party data centers, strategic partners, and industrial infrastructure environments. We focus on converting power, land, hardware, and operational execution into reliable compute capacity that can support frontier AI training and inference workloads. This team operates at the intersection of infrastructure delivery, hardware systems, utilities, supply chain, and capacity strategy—ensuring OpenAI can scale compute faster than traditional models allow. About the Role We are seeking a Tokens-as-a-Service (TaaS) Lead to drive the end-to-end conversion of industrial-scale infrastructure investments into usable token capacity for OpenAI workloads. In this role, you will own execution across complex compute programs where raw infrastructure capacity must be transformed into operational GPU throughput. You will coordinate across data center delivery, power, networking, hardware deployment, workload enablement, finance, and external partners to ensure capacity becomes productive tokens as quickly and efficiently as possible. This role is ideal for someone who can bridge physical infrastructure delivery with compute utilization outcomes. Success requires strong systems thinking, elite program leadership, and the ability to drive accountability across internal teams and strategic partners. In this role, you will Lead Tokens-as-a-Service programs across industrial compute environments, including first-party and partner-owned capacity. Convert delivered power, space, and hardware capacity into production-ready token throughput. Build integrated execution plans spanning construction, power energization, rack deployment, networking, cluster readiness, and workload onboarding. Partner with infrastructure engineering, hardware, networking, finance, supply chain, and operations teams. Drive external providers, EPCs, OEMs, utilities, and strategic partners t

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. ABOUT THE TEAM: We exist to improve Product leaders’ understanding and decision-making on how to profitably grow the business. Our North Star is to increase workload contribution margin dollars above the current forecast by serving as an objective, full-stack business partner. We do this by measuring key metrics, inferring actionable insights, catalyzing strategic decisions, and accelerating operational efficiency across Product, Engineering, and Sales. ABOUT THE ROLE: This is a high-visibility role that sits at the intersection of product strategy and financial analysis, giving you a unique vantage point to influence how we scale our business. We aren't looking for someone to just execute tasks and pull data; we need a partner who can navigate ambiguity, drive workstreams, and anticipate the next steps. This role is best for proactive problem-solvers with business intuition and a high level of curiosity. You will work on critical projects and collaborate with executives to turn complex data into decisive action. WHAT YOU WILL DO: Develop & Maintain Financial Models: Build and iterate on financial models that track both revenue and cost drivers, enabling accurate forecasting and real-time visibility into workload contribution margins. Drive Revenue & Margin Insights

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 redefining how enterprises bring data, applications, and AI together. As autonomous workflows begin taking actions on behalf of users, identity has officially become the new security perimeter. Every single interaction—whether initiated by a human, an application, a workload, or an AI agent—must be continuously authenticated, authorized, and governed. To unlock this next generation of enterprise software, Snowflake requires an identity platform that extends far beyond traditional workforce authentication to seamlessly support machine identities, fine-grained delegation, and policy-driven access at cloud scale. We are looking for a hands-on, high-impact Product Leader to define and build this foundational trust layer. Operating at a highly strategic intersection of product, engineering, partnerships, and executive-level customer engagement , you will own the core infrastructure that allows complex enterprise systems to securely interact, reason over sensitive data, and safely execute actions. AS A PRINCIPAL PRODUCT MANAGER AT SNOWFLAKE, YOU WILL : Set Portfolio Strategy: Own and define the long-term product strategy and roadmap for Snowflake’s IAM ecosystem, factoring in market-shifting competitive trends and technical evolutions. Build for AI era: Architect IAM

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. The Logistics Security Intelligence Analyst supports Micron’s global logistics security program by producing timely, actionable intelligence on shipment risk, cargo theft trends, route exposure, carrier performance, alert activity, and logistics security incidents. This individual contributor role helps strengthen shipment visibility, support incident response, and enable data-driven decisions for valuable and sensitive shipments across Micron’s transportation network. Responsibilities: Collect, analyze, and report on logistics security data related to high-value and high-risk shipments, including shipment value, route risk, carrier performance, tracking status, alert activity, and incident history. Monitor internal, vendor, industry, open-source, and law-enforcement sources for cargo theft trends, route disruptions, regional security developments, and emerging threats. Prepare intelligence summaries, dashboards, route profiles, regional threat updates, incident trend reports, and briefing materials for logistics security leaders and multi-functional collaborators. Support lane, route, carrier, provider, and regional risk assessments by identifying risk indicators, documenting findings, and helping translate analysis into practical control recommendations. Analyze shipment monitoring alerts such as route deviation, unauthorized stop, signal loss, seal breach, geofence violation, cargo separation, and other logistics security events. Support blocking issue and incident response a

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: We are currently seeking a Quantitative Risk Analysis Manager to join the Credit Analytics & Reporting team in the Single-Family division. This position will be tasked with managing a team responsible for reporting and analytics regarding Collateral offerings as well as Collateral model business user supports. The role requires deep understanding of data and current code base, designing analytical approaches for business questions and scenario evaluations, managing data research, analyses and preparation of reports and presentations. Our Impact: Our team is responsible for producing reporting packages to monitor trends and performance. We analyze different test and learn or pilot programs to assess risk of the offerings and create reports to monitor these offerings closely to assess broad roll out. We perform significant user activities for enterprise Collateral models for user acceptance testing and provide feedback. Your Impact: Manage a team of three to four people Complete baseline processes and reports monthly and interpret results as it relates to collateral risk management Follow appropriate controls and standards established to maintain and document for processes & reports. Participate in performing ad-hoc analytics in support of collateral policy Cleanse, manipulate and analyze large datasets using statistical software Collaborate with team members and interact across organizational lines to meet business objectives Qualifications: Degree in

Become a part of our caring community Do you thrive on designing secure, enterprise-scale solutions that protect critical systems, data, and networks? As a Lead Security Architect in Humana, you will play a key role in shaping the security blueprint for the organization by aligning security architecture and infrastructure with enterprise business and technology priorities. In this role, you will partner with EIP and business leaders to assess emerging threats, identify architectural gaps, and design forward-looking security solutions that strengthen Humana's overall security posture. You will also lead security assessments, vulnerability analysis, and product security reviews while helping develop innovative testing approaches and mitigation strategies for evolving risks. This is a high-impact opportunity to influence enterprise architecture, guide secure technology design, and help protect the business through strategic, modern security architecture. The Lead Security Architect engages with relevant EIP stakeholders to identify current and emerging security threats and works to design security architecture elements to mitigate threats as they emerge. Additionally, the role actively works to identify gaps within existing EIP reference architecture and designs updates to impacted security architecture elements to mitigate emerging threats. Performs and oversees efforts to conduct vulnerability testing, risk analysis, and security assessments of relevant enterprise / EIP infrastructure. Ensures EIP and Humana stakeholder security requirements are necessary to protect Humana's business functions and are adequately addressed in all aspects of enterprise architecture. The Lead Security Architect role is aligned to a segment (line of business) to proactively discover security issues during solution design and prevent vulnerabilities during development.

Become a part of our caring community Humana’s Quality and Cost Strategy Analytics Team is seeking a Research Scientist 2 (Remote). Healthcare is rapidly changing, and our members are living longer, often with more chronic conditions. The Quality and Cost Strategy Analytics team identifies opportunities and build solutions to improve clinical outcomes and lower costs for millions of Medicare Advantage beneficiaries leveraging data science & analytics, clinical expertise, strategic mindset, and rigorous study designs. In this multi-disciplinary team, you will have the opportunity to work closely with strategy partners and clinicians to shape Humana’s future enterprise clinical strategies and initiatives. The Research Scientist 2 will lead research, evaluation and development of opportunities that optimize healthcare delivery, lower medical cost while improve member health outcomes, through applying mathematical, statistical, epidemiologic and data science methods. The Research Scientist 2 will also partner with stakeholders across the enterprise to identify, prioritize and measure the impact of core and novel solutions to significant problems in healthcare and improve the health of especially underserved population, using high volumes of structured and unstructured data. Responsibilities As a Research Scientist 2, you will: Research, prototype and scale new ideas to improve population health and healthcare delivery Collaborate with analytic and business teams to set objectives, approaches, and work plans Collaborate with strategy to evaluate existing programs and identify and measure new solutions to impact healthcare Leverage a wide range of analytics methods ranging from descriptive to prescriptive to transform high volumes of complex data into analytics solut

Become a part of our caring community The Associate Vice President, Model & AI Governance, is the enterprise leader responsible for establishing and overseeing the organization’s framework for model governance, artificial intelligence (AI) risk management, responsible AI and AI governance. Reporting to the Chief Audit & Risk Officer, this executive provides independent second-line oversight and challenge of the organization’s use of models, advanced analytics, machine learning, generative AI, and emerging AI technologies. The role establishes the governance, risk-management, control, monitoring and escalation framework necessary to ensure AI models are deployed in a manner that is safe, ethical, transparent, explainable, compliant, secure and aligned with the organization’s mission and risk appetite. The Associate Vice President, Model & AI Governance, partners closely with executive leadership, technology, data and analytics, clinical/business leaders, compliance, legal, privacy, cybersecurity, information security, internal audit, enterprise risk management and other control functions to ensure AI-related risks are identified, assessed, governed, monitored, and appropriately reported. This leader will serve as an advisor to executive management on emerging model and AI risks, while maintaining appropriate independence from the teams developing and deploying models and AI solutions. Key Responsibilities Own and continuously enhance the enterprise model governance framework, including model identification, inventory, classification, risk tiering, development, validation, approval, implementation, monitoring, change management, retirement and documentation. Define model risk appetite, risk taxonomy, minimum control standards, governance requirements and escalation thresholds. Provide effective challenge over model