Signal And Growth Insights Manager Jobs

About the Team OpenAI’s Network Engineering team within IT and Security advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient network services. We build and operate the connectivity that supports OpenAI’s offices, labs, campuses, cloud environments, people, and devices. By combining strong network fundamentals with security, reliability, automation, and user-centered design, we enable impactful AI research, corporate operations, and product innovation. About the Role As a Network Engineer at OpenAI, you will design, operate, and continuously improve the global networks that connect our offices, labs, campuses, PoPs, cloud environments, people, and devices. The role spans strategic platform engineering and responsive production operations: you will shape architecture, standards, roadmaps, lifecycle plans, and automation while supporting incidents, escalations, and time-sensitive delivery. Operational signals will inform what we stabilize, simplify, standardize, or automate next. We work backward from user needs, investigate root causes, own outcomes end-to-end, and move quickly without compromising security. We are looking for a versatile engineer who can make pragmatic reliability and security tradeoffs, communicate clearly, and turn recurring operational work into durable platforms, tooling, and standards. You will partner across IT, Security, AppEng, Research, Applied, workplace teams, carriers, and vendors. In this role, you will: Design, implement, and operate secure, scalable enterprise networks across offices, labs, campuses, PoPs, cloud connectivity, and hybrid environments. Set strategic direction for network services through architecture, standards, roadmaps, lifecycle planning, capacity strategy, and measurable reliability outcomes. Own production operations, including on-call, incident response, escalations, and time-sensitive delivery, while protecting user experience,

About the Team The CoT Monitorability team at OpenAI studies whether and when the chain-of-thought of frontier reasoning models is monitorable enough to support scalable oversight. We study how to measure monitorability , which training mechanisms affect monitorability, and speculative methods to improve monitorability. While we mostly focus on CoT monitorability at the moment, we care more generally about any form of monitorability, auditing methods, and improving alignment. We were the first to show that chain-of-thought monitoring can be a practical additional safety mechanism, and today our monitoring systems are actively used on OpenAI’s largest RL training runs to detect misbehavior. The issues we surface are then used to help improve our reward functions, environments, etc (without directly training against a CoT monitor). Our work sits in Alignment and intersects with model training, alignment evaluations, monitoring, and frontier-risk research.We care most about monitorability where the stakes are high, and about preserving useful oversight signals as models become more capable. About the Role We’re looking for a researcher with strong empirical ML expertise and a deep interest in model behavior, alignment, or interpretability. Direct chain-of-thought interpretability experience is welcome but not required; strong candidates may come from broader interpretability, alignment, model training, or investigative model-behavior work. As a researcher on the Alignment team, you will design and run experiments that improve our understanding of model monitorability. You will investigate how training interventions across the model-development pipeline influence whether reasoning remains legible, build evaluations that make those questions measurable, and help translate findings into practical oversight and training recommendations. You may also help develop new monitoring models or methods and apply them to OpenAI’s largest training runs. This role is especially well

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: You'll be Recruiting's dedicated people analytics partner — owning the data, shaping the strategy, and in the room where decisions get made. The core of the role is building trusted recruiting analytics infrastructure (funnel + stage conversion, pipeline aging, time-to-fill, offer acceptance, sourcing channel quality, and recruiter capacity) and making it self-serve for recruiters and leaders. You’ll own the stack end-to-end — from raw data in Ashby and Snowflake to clear insights that hold up in a pipeline review. You're the person who turns workforce signals into recruiting strategy — bringing a point of view. This role may be based in either our San Francisco or New York City offices. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Own recruiting analytics end-to-end: Build and maintain the dashboards and reporting infrastructure Recruiting leadership relies on (funnel health, conversion rates by stage, time-to-fill,

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. About our Customer Platform team: Our Customer Platform Team plays a pivotal role in integrating our platform with external systems and ensuring seamless, reliable connectivity for both internal users and customers. As the leader of this team, you’ll drive the strategy, architecture, and development of our connectivity solutions, focusing on API integration, distributed systems, and a robust data platform. Your role will be crucial in maintaining and enhancing our platform’s ability to meet the needs of both our internal and external stakeholders. Responsibilities: Own large areas within our product Comfortable working cross functionally, whether that be internal or external customers Build features end-to-end: front-end, back-end, system design, debugging and testing Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Influence the culture, values, and processes of a growing engineering team Inspire and mentor less experienced engineers Collaborating with cross-functional teams to define, design, and ship new product features and experiences. Requirements: At least 7-10 years of relevant experience is preferred Track record of shipping high-quality products and features at scale Desire to work in a very fast-paced environment Abil

About the Team DoorDash is looking for an Engineering Manager to lead our Discovery Experience team, which owns the Homepage - DoorDash’s front door. It’s the first screen millions of consumers see every day, and since every session starts there, it’s the highest-leverage surface in the consumer funnel: a more personalized recommendation, a faster render, or a cleaner layout can move the metrics the whole company watches. The Homepage spans restaurants, grocery, and emerging verticals across iOS, Android, and Web. We’re rebuilding it around LLM-generated recommendations, shifting discovery from static, rules-based feeds to generative, intent-driven experiences that respond to real-time signals in the moment. About the Role You will lead and grow a team of product-focused full stack engineers, owning both the product and technical direction for the discovery surface - deciding where discovery goes next and how it’s built. You’ll set the roadmap and drive execution alongside Product, Design, Data Science, and ML/Recommendation Platform partners, and you’ll own the quality, velocity, and consumer impact your team ships. It’s a role with real ownership and the room to grow both the product and the team behind it. You’re excited about this opportunity because you will… Own the Homepage end to end, the highest-traffic surface at DoorDash and where every consumer session begins Turn Homepage bets into company-level outcomes: real lift in conversion and order rate for millions of consumers Define discovery quality for DoorDash: getting the right store, restaurant, or item in front of the right consumer at the right moment Ship LLM-gen recommendations and intent-aware discovery that route consumers to the right experience across food, grocery, retail, and emerging verticals Partner across Product, Design, Data Science, and ML/Recommendation Platform teams to shape the discovery roadmap and ship the experiences behind it Build an inclusive, high-performing team by coaching en

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. As a Data Scientist on the Mapping team, you will collaborate with our world class team of scientists, engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our geospatial, behavioural and mobility data, and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers. Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. The Mapping team serves models and systems that determine the most efficient routes, fastest travel estimates and process real-time map data signals to detect traffic, closures and slowdowns. Working with our business and analytics partners, the team owns tools to ensure Lyft offers routes that our users trust. This will involve identifying and scoping opportunities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in Mapping, including: How do we accurately predict acute and chronic traffic conditions? How do we improve the recommendations of our routing algorithms? How do we keep our travel estimation promises to our riders and drivers? How do we benchmark and measure the success of our services? Responsibilities: Own the complete lifecycle of algorithmic solutions from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration Prioritize and lead deep dives into our data to uncover new product and business opportunities Partner closely with E

About the Team OpenAI’s acquisition of io marks our entry into consumer hardware and our ambition to define the next human–computer interface. Success in hardware requires strong financial stewardship across the full product cost stack—from early design and sourcing decisions through manufacturing, logistics, inventory, returns, and warranty. Hardware Finance works across Product, Supply Chain, Operations, Accounting, Systems/Data, and Finance to connect business decisions to product cost, inventory, cash, COGS, and margin. About the Role We are seeking a Hardware Finance Manager to own an assigned area of hardware COGS and inventory end to end. The initial assignment will depend on business priorities and the successful candidate’s expertise. It may include BOM and product cost, manufacturing variance analysis, inventory planning, logistics, returns and warranty, customer support, or another connected set of hardware-finance responsibilities. This is an individual-contributor role with broad scope. Prior hardware experience and deep, hands-on expertise in at least two relevant domains are required. The person will be expected to operate independently, build reusable processes and analytical workflows, and remain accountable for the analysis, judgment, and recommendations. In this role, you will: Own an assigned area of hardware COGS and inventory end to end. Own forecasting, close, and business variance analysis for the assigned scope. Provide hardware leadership with clear variance explanations, trend analysis, and forward-looking signals that connect business and supplier decisions to inventory, cash, COGS, and margin. Partner with business teams and Finance Platforms to establish the financial data, systems, and dashboards needed to support analysis. Ensure data integrity and governance through clear definitions, ownership, validation checks, controls, and review processes. Improve forecasting, reporting, systems, and finance processes so they remain reliable an

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Software Engineers at Palantir drive large-scale transformation through data, AI and world-leading infrastructure that supports mission-critical workloads. As an engineer within Palantir's Infrastructure teams, you'll have the opportunity to grow more quickly than you ever imagined as you contribute high-quality code directly to: The shared infrastructure underpinning Palantir Foundry, Palantir Gotham and Palantir Apollo — platforms deployed at the most important institutions across the public and private sectors Rubix and Mission Manager, our new internal-infrastructure business line, used by advanced civil and defence agencies worldwide to power their infrastructure in highly sensitive environments The substrate on which Palantir deploys Foundry and Gotham, powering workflows for research scientists, aerospace engineers, intelligence analysts and economic forecasters This means driving investments that improve the velocity and quality of our engineering. Infrastructure at Palantir spans our Foundations, Production Infrastructure and Foundry teams. Teams within Palantir's Foundations organisation are made up of a small number of engineers, each focused on one of four major categories of our infrastructure: Backend Infrastructure Developer Infrastructure Frontend Infrastructure Storage Infrastructure Production Infrastructure organisation, made up of small teams of engineers working on: Environment Platform: a Kubernetes-based PaaS spanning hundreds of production clusters Apollo: secure, fleet-wide deployment and change-management for complex microservice suites Signals: our full suite of observability and alerting tools Foundry itself is also a developer

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Software Engineers at Palantir drive large-scale transformation through data, AI and world-leading infrastructure that supports mission-critical workloads. As an engineer within Palantir's Infrastructure teams, you'll have the opportunity to grow more quickly than you ever imagined as you contribute high-quality code directly to: The shared infrastructure underpinning Palantir Foundry, Palantir Gotham and Palantir Apollo — platforms deployed at the most important institutions across the public and private sectors Rubix and Mission Manager, our new internal-infrastructure business line, used by advanced civil and defence agencies worldwide to power their infrastructure in highly sensitive environments The substrate on which Palantir deploys Foundry and Gotham, powering workflows for research scientists, aerospace engineers, intelligence analysts and economic forecasters This means driving investments that improve the velocity and quality of our engineering. Infrastructure at Palantir spans our Foundations, Production Infrastructure and Foundry teams. Teams within Palantir's Foundations organisation are made up of a small number of engineers, each focused on one of four major categories of our infrastructure: Backend Infrastructure Developer Infrastructure Frontend Infrastructure Storage Infrastructure Production Infrastructure organisation, made up of small teams of engineers working on: Environment Platform: a Kubernetes-based PaaS spanning hundreds of production clusters Apollo: secure, fleet-wide deployment and change-management for complex microservice suites Signals: our full suite of observability and alerting tools Foundry itself is also a developer

Manager I, Engineering - Change Experience Platform The Change Experience Platform team builds the internal experiences and platform capabilities that help Datadogs understand, author, route, and safely manage infrastructure changes. The team owns internal UI and CLI frameworks, change-management user experiences, notification and subscription platforms, and infrastructure governance signals used across Datadog’s engineering organization. Its work sits at the intersection of developer experience, infrastructure operations, product design, and change safety. We’re looking for a hands-on technical leader to manage and grow a team of engineers working on the systems that shape how Datadog engineers interact with infrastructure change. You will partner closely with infrastructure, developer experience, platform engineering, and product teams to build reusable interfaces, workflows, and safety mechanisms that make complex change processes easier to understand and safer to execute. This is a high-impact role for someone who enjoys combining product thinking with strong engineering judgment. You will help the team balance framework ownership, platform reliability, internal customer needs, and long-term technical direction across a portfolio that includes UI systems, CLI authoring and publishing, change-management workflows, notification routing, subscriptions, and infrastructure cordon management. 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: Lead and grow a small team of engineers responsible for internal platforms and product experiences used across Datadog engineering. Help define what “good” looks like for internal developer-facing platforms, including usability, reliability, documentation, adoption, and supportability. Se

MongoDB is growing its team in Sydney, focusing on building intelligent tools that help customers understand and modernise their application codebases. The Application Modernisation Platform (AMP) guides customers through the entire journey of modernising their applications — from legacy relational platforms to modern, scalable systems built on MongoDB. The App Analysis & Modelling team owns the critical first stage of this journey: building the context that powers everything downstream. The team builds code analysis tools that construct code dependency graphs and generate deep insights for codebases, giving customers a clear understanding of their existing applications before transformation begins. The team also designs schema recommendation engines that analyse signals such as existing relational schemas and query patterns to inform data modelling decisions. Our work sits at the intersection of analysis, data modelling, and AI — helping developers make confident, data-driven decisions as they transition to MongoDB. We are looking for a Software Engineer who is passionate about building scalable backend systems and applications. As we expand our use of AI to power smarter analysis and recommendations, the ideal candidate will bring strong backend engineering fundamentals with the ability to contribute across the full stack. You will collaborate closely with product management and other engineering teams to design and deliver cutting-edge features that guide customers through complex modernisation journeys. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The Ideal Candidate Will Have 3+ years of commercial software development experience with strong proficiency in Python and/or Java Experience designing and building scalable, high-performance APIs and backend services Solid understanding of relational data modelling and SQL (Oracle, PostgreSQL, MySQL, or similar), including schema design and query optimisation Good und

MongoDB is growing its team in Sydney, focusing on building intelligent tools that help customers understand and modernise their application codebases. The Application Modernisation Platform (AMP) guides customers through the entire journey of modernising their applications — from legacy relational platforms to modern, scalable systems built on MongoDB. The App Analysis & Modelling team owns the critical first stage of this journey: building the context that powers everything downstream. The team builds code analysis tools that construct code dependency graphs and generate deep insights for codebases, giving customers a clear understanding of their existing applications before transformation begins. The team also designs schema recommendation engines that analyse signals such as existing relational schemas and query patterns to inform data modelling decisions. Our work sits at the intersection of analysis, data modelling, and AI — helping developers make confident, data-driven decisions as they transition to MongoDB. We are looking for a Senior Software Engineer who is passionate about building scalable backend systems and applications. As we expand our use of AI to power smarter analysis and recommendations, the ideal candidate will bring strong backend engineering fundamentals with the ability to contribute across the full stack. You will collaborate closely with product management and other engineering teams to design and deliver cutting-edge features that guide customers through complex modernisation journeys. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The ideal candidate will have 5+ years of commercial software development experience with strong proficiency in Python and/or Java Extensive Experience designing and building scalable, high-performance APIs and backend services Solid understanding of relational data modelling and SQL (Oracle, PostgreSQL, MySQL, or similar), including schema design and query opti

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 Media is extending the value of Lyft's first-party rider data beyond our owned-and-operated surfaces. Through our Audience Solutions business, agencies and brands activate Lyft audiences across the open web, CTV, social, and DSPs — powered by one of the most distinctive mobility datasets in the US. We're hiring an Account Executive to grow this business across agency and holding company accounts. Responsibilities: Own a book of agency and holdco accounts — prospect, pitch, negotiate, and close data licensing and off-platform audience activation deals (Lyft audiences syndicated to DSPs, SSPs, and partner platforms — not Lyft-owned inventory) Build relationships across investment, planning, data strategy, and programmatic trading desks at major holdcos (GroupM, Omnicom Media Group, Publicis Media, IPG, Dentsu, Horizon, Stagwell, etc.) Hit and exceed quarterly revenue targets Translate Lyft's first-party mobility data into briefs that win RFPs — audience segments, geo/movement signals, and measurement use cases Partner with Account Management, Data Partnerships, and Product to ensure clean activation, attribution, and renewal Maintain accurate pipeline hygiene in Salesforce and forecast with discipline Experience: 3–5 years of digital media or data sales experience, with meaningful exposure to programmatic (PMP, PG, open exchange) and/or agency holdco accounts Track record of closing and growing agency business Comfortable with the alphabet soup: DSPs (DV360, TTD, Yahoo), SSPs, data clean rooms (LiveRamp, Habu, AWS), IDFA/MAID/postal-code targeting, MMM and incrementality conversations Strong written and verbal communication; can build a deck and run a meeting Hungry, organized, and coachable Preferred: Direct experience selling audience data, data licensing, or off-platform activation (ex-LiveRamp

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's Customer Care Operations organization manages over 1.7 million monthly customer interactions and serves as the company's primary direct touchpoint with riders, drivers, and businesses — spanning frontline support across multiple customer segments, a global BPO workforce, and the central functions that enable them to operate at scale. The Senior Manager of Support Excellence owns the enablement infrastructure that determines whether Lyft's support operation can scale efficiently, react nimbly, and maintain high standards: Knowledge Management, Quality, Learning & Performance, and Tooling Enablement. This is not a role for someone who wants to maintain and optimize — it's a role for someone who wants to reimagine. The right person brings a bold, integrated vision for how these functions work together with Operations, Product, and Technology to improve customer outcomes and accelerate Lyft's evolution into an AI-native, human-enhanced support organization. They will set the direction, hold the bar, and move at the pace the environment demands — with the industry expertise to know what "great" looks like and the conviction to pursue it. Reporting to the Director of Business Planning & Central Operations, this role leads a team of 4-6 direct reports and 40-50 indirects, each owning a distinct function on the team team. Responsibilities: Vision & Strategy Define and own an ambitious, integrated vision for how Knowledge Management, Quality, Learning & Performance, and Tooling Enablement work together — not as separate functions, but as a unified enablement system that improves customer outcomes and advances Lyft's AI-native support evolution. Expand active AI fluency to every function in the portfolio — from how knowledge is structured for AI retrieval, to how quality signals feed mod

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's Customer Care Operations organization manages over 1.7 million monthly customer interactions and serves as the company's primary direct touchpoint with riders, drivers, and businesses — spanning frontline support across multiple customer segments, a global BPO workforce, and the central functions that enable them to operate at scale. The Senior Manager of Support Excellence owns the enablement infrastructure that determines whether Lyft's support operation can scale efficiently, react nimbly, and maintain high standards: Knowledge Management, Quality, Learning & Performance, and Tooling Enablement. This is not a role for someone who wants to maintain and optimize — it's a role for someone who wants to reimagine. The right person brings a bold, integrated vision for how these functions work together with Operations, Product, and Technology to improve customer outcomes and accelerate Lyft's evolution into an AI-native, human-enhanced support organization. They will set the direction, hold the bar, and move at the pace the environment demands — with the industry expertise to know what "great" looks like and the conviction to pursue it. Reporting to the Director of Business Planning & Central Operations, this role leads a team of 4-6 direct reports and 40-50 indirects, each owning a distinct function on the team team. Responsibilities: Vision & Strategy Define and own an ambitious, integrated vision for how Knowledge Management, Quality, Learning & Performance, and Tooling Enablement work together — not as separate functions, but as a unified enablement system that improves customer outcomes and advances Lyft's AI-native support evolution. Expand active AI fluency to every function in the portfolio — from how knowledge is structured for AI retrieval, to how quality signals feed mod