Collection Manager Jobs

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as our next Software Engineer on Twilio’s platform engineering observability team. About the job This position is needed to help our platform engineering observability team. Twilio is undergoing a large-scale observability transformation—and you can help shape the foundation. Observability is a strategic pillar and a key enabler for faster incident response, deeper customer-centric insights, and more cost-effective platform operations. As a Software Engineer on the Platform Observability team, you’ll play a critical role in re-architecting how telemetry flows and is utilized through Twilio—making it structured, accessible, affordable, and actionable. Over the next 3 years, Twilio is rebuilding nearly every component of our observability platform, from data collection to real-time analytics. You will drive core initiatives that shift Twilio from fragmented tooling and wasteful data sprawl to a unified, OpenTelemetry-first observabil

The Team: As a Security Engineer 2 on the Cyber Threat Intelligence team, you will help Datadog stay ahead of evolving threats by identifying, analyzing, and operationalizing intelligence on threat actors, campaigns, and emerging threats. Working within Security Engineering, you will partner closely with security teams to translate intelligence into actionable security improvements across the company. You will serve as a subject matter expert on how the cyber threat landscape intersects with Datadog and contribute to intelligence-led decision making during both steady-state operations and active security incidents. This role provides opportunities to influence detection, response, and security strategy through technical analysis, collaboration, and intelligence-driven initiatives. 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: Develop and maintain tooling that automates the collection, processing, analysis, and dissemination of threat intelligence. Assess emerging vulnerabilities, threat activity, and security events to help stakeholders understand potential impact to Datadog. Conduct threat hunting and infrastructure analysis to identify adversary activity relevant to Datadog and improve defensive controls. Partner with security teams to operationalize intelligence into detections, investigations, and response workflows. Coordinate with information-sharing communities to gather, evaluate, and disseminate actionable intelligence. Produce technical briefings, threat reports, and intelligence products for security and engineering stakeholders. Who You Are: Experienced in writing and presenting operational and technical intelligence for threat detection, response, and security stakeholders. Skilled in partnering with detection and response te

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Stripe Infrastructure is responsible for the reliability, scale, performance, and cost of Stripe's systems and the productivity and sentiment of Stripe's people. You may work on a wide variety of critical business areas including: Core Infrastructure—We're the home for Stripe's critical tier0 infrastructure systems (Compute, Networking, DocumentDB, Distributed Caching and High assurance engineering). We build the foundational platform for Stripe products and services to allow them to operate at scale. We drive reliability, availability, efficiency, and scalability of these systems. Developer Infrastructure—We're responsible for the productivity of all developers at Stripe. Ensure Stripe's engineers have a reliable, fast, and easy-to-use inner dev loop to maximize productivity while building everything from low-latency microservices to large-scale data pipelines and machine learning models. Data Infrastructure—We're responsible for offering data serving infrastructure spanning across data warehouse analytics, streaming analytics, and search capabilities. The stack is supported by a collection of internally developed large-scale distributed services and several popular open-source technologies like Trino/Presto, Apache Pinot, Hive Metastore, ElasticSearch etc. The systems we own support all of the data serving needs of high-scale services and thousands of individual Stripes across the company. Admin Platform—We empower Stripes to quickly

At Bolna, we’re building tools that change the way teams leverage Voice AI. We’re looking for a Founding Machine Learning Engineer to own the end-to-end lifecycle of building, evaluating, deploying, and improving models that power millions of production conversations. This is a high-impact, high ownership role where you won’t just work on Bolna’s ML stack—you’ll help build the foundation it scales on. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities: Build the data engine - Design pipelines to source and clean conversational voice data across Indian languages, accents, and telephony conditions. Fine-tune models that ship - Fine tune and train models to improve accuracy, speed, and reliability across different use-cases. Define what "good" means - Build evaluation datasets and benchmarks for transcription accuracy, voice naturalness, interruption handling, latency, and end-to-end conversation quality. Set up human-in-the-loop pipelines to capture subjective quality at scale. Ship to production - Work with the engineering team to deploy models into a latency-sensitive, high-volume system. Monitor performance in the wild, debug regressions, and iterate fast. Required Skills: 3+ years of hands-on ML experience with deep practical real-world experience in training models. Strong Python and PyTorch fundamentals with exposure in distributed training, and modern fine-tuning techniques (LoRA, QLoRA, DPO, RLHF, etc.). Training data as a first-class problem. Experience designing data pipelines from collection, cleaning, labeling, deduplication, augmentation and treating data quality as a core engineering discipline. Rigorous about evaluation. You know that "looks good in a demo" is not a benchmark. You build the evals before you trust the model. Speech model experience is a plus with real-time / streaming inference experience where you would have contributed to latency optimization

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role OpenAI is seeking to build an investigative capability for Secure Manufacturing & Stealth programs. The risk surface for unreleased products, prototypes, confidential hardware, infrastructure, supply chain, manufacturing, and launch-readiness efforts spans employees, vendors, suppliers, logistics partners, physical movement of assets, procurement records, manufacturing workflows, access systems, device telemetry, and adversarial collection. This role is intended to build and run investigations across that specialized environment. In this role, you will: Lead complex SMS investigations to proactively identify and mitigate risks to unreleased products, prototypes, confidential hardware, secure manufacturing programs, and launch-readiness efforts. Investigate unauthorized disclosure, suspected leaks, insider risk, supplier compromise, vendor misconduct, theft, diversion, tampering, counterfeiting, surveillance, adversarial collection, and suspicious activity involving sensitive programs. Connect digital evidence, physical access activity, supply chain records, manufacturing data, vendor behavior, employee activity, collaboration metadata, procurement records, shipping data, and OSINT into clear findings and risk-reduction actions. Conduct proactive threat hunting to surface early indicators of compromise, collection, leakage, or insider activity affecting sensitive programs. Develop investigative playbooks, evidence-handling standards,

About the Team The Monetization team is a cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. In this foundational role, you’ll design infrastructure for conversion signals, attribution, reporting, and feedback loops across OpenAI’s ads products. This role is ideal for engineers who have built large-scale ads measurement, data, experimentation, marketplace, or distributed systems and want to apply that experience in a highly ambiguous 0→1 environment. You’ll work across event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy-safe aggregation, reporting, and high-quality labels for ads optimization. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You’ll work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Sc

About the Team OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort. The Human Data engineering team creates the systems that enable scalable, high-quality human feedback. These systems are essential to how OpenAI trains and improves its most advanced models. Engineers on this team collaborate closely with world-class researchers to bring alignment techniques to life — from experimental ideas to production-ready feedback loops. About the Role We’re looking for software engineers to join the Human Data team and build the platforms, prototypes, tools, and infrastructure that power how our AI models are trained, aligned, and evaluated. You’ll partner with researchers and cross-functional teams to bring alignment ideas to life, influence future model training, and shape how models interact with the real world. We’re looking for people who are excited by technical ownership, enjoy working across the stack, and are eager to solve ambiguous problems in a high-impact, fast-paced environment. 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: Build and maintain robust full-stack systems for feedback collection, data labeling, and evaluation pipelines, while maintaining high levels of security. Translate experimental alignment research into scalable production infrastructure, including inference and model training stacks. Design and iterate on user-facing tools and backend services to support high-quality data workflows Partner with researchers, engineers, and program leads to shape feedback loops and model interaction paradigms Drive infrastructure improvements that enable faster iteration and scaling across OpenAI’s frontier models, from internal r

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are hiring a Sim Infrastructure Engineer to turn simulation systems into reliable, automated, production-quality pipelines that power model training, evaluation, and hardware-in-the-loop validation. This role owns the automation, orchestration, and tool integration that apply simulation to concrete robotics tasks: building CI/CD for SIL/HIL, presubmit checks, automatic model evaluation, metric computation and reporting, and the runtime infrastructure to run simulations at scale. You will collaborate closely with Sim Realism, Sim Environments, Research, and Ops to make simulation an integrated, reproducible, and measurable part of our ML and robotics workflows. This role is based in San Francisco, CA, and requires in-person 4 days a week. In this role, you will: Build and maintain presubmit checks, continuous integration and deployment pipelines for simulation code, environments, and tasks so simulation artifacts are testable, versioned, and reproducible. Implement end-to-end automation to run model evaluation in sim (SIL) and orchestrate HIL runs; compute realism and task metrics, generate dashboards and alerts, and ensure evaluation is repeatable and auditable. Create robust APIs and connectors so research, training, and data-collection systems can schedule, seed, and evaluate batches of simulations; support RL rollouts, imitation-data collection, and presubmit model checks. Build scheduling, batching and orchestration for running very large numbers of concurrent rollouts (target tens of thousands of rollouts / large RL workloads), sol

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Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Job Title Collections Specialist II Working at Abbott At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You’ll also have access to: Career development with an international company where you can grow the career you dream of. Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year. An excellent retirement savings plan with a high employer contribution. Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree. A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune. A company that is recognized as one of the best big companies to work for as well as the best place to work for diversity, working mothers, female executives, and scientists. The Opportunity This position works out of our Lake Mary, Florida location in the Abbott Heart Failure, Acelis Connected Health business. Our Heart Failure solutions are

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Job Title Collections Specialist II Working at Abbott At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You’ll also have access to: Career development with an international company where you can grow the career you dream of. Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year. An excellent retirement savings plan with a high employer contribution. Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree. A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune. A company that is recognized as one of the best big companies to work for as well as the best place to work for diversity, working mothers, female executives, and scientists. The Opportunity This position works out of our Lake Mary, Florida location in the Abbott Heart Failure, Acelis Connected Health business. Our Heart Failure solutions are

Representative 1, Credit & Collections - Commercial — Virtual. Apply via Workday.

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 Collections Experience owns the product experience for Notion’s database block and everything on top of it: properties, views, forms, permissions, and many more features. If you’ve ever typed /database in a Notion page, you’ve already used something our team built. We’re hiring an experienced software engineer to accelerate our mission to build a flexible, reliable, and intuitive primitive that gives everyone the power to model their work exactly as they imagine— from simple lists to the most complex workflows. We’re 8+ engineers, designers, and PMs across SF and NYC. You’ll work across the stack in TypeScript, ship features that touch both the data model and the UI, and help shape where the database block goes next. What You'll Achieve Design and ship new database properties and views that expand what people can model in Notion Design permission models that hold up at the scale of our largest customers Partner with the Agent team to grow what Notion Agent can do with databases, from tool development to eval-driven iteration Collaborate closely with product and design on features that are ambiguous up front and require

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: As a Software Engineer on Collections Infra, you’ll help scale the infrastructure behind Notion’s database block. Databases power views, boards, charts, forms, and the workflows customers use to run their companies; as Notion grows into larger enterprise deployments and AI-native work, those systems need to become faster, more reliable, and ready for much higher concurrency. This team sits between infrastructure and product, building backend architecture that improves the customer experience while becoming a platform other Notion teams can build on. You’ll work on problems like database load performance, microservices, high-volume writes from agents, and the flexibility that makes Notion databases powerful and hard to scale. This role can be based in either San Francisco or New York City. 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: By your 90th day, you’ll understand how Collections Infra supports Notion’s database

About Bolna Bolna is a YC-backed voice AI orchestration platform built for the Indian market—powering multilingual, vernacular voice agents across Hindi, Hinglish, Tamil, and 10+ languages at sub-500ms latency across collections, recruitment, sales, and e-commerce use cases. We are an orchestration layer, not a model company: our moat is outcome-labelled vernacular data, rigorous evaluation infrastructure, and a growing taxonomy of how Indian enterprise voice AI fails in production. Why This Role Exists Product decisions at Bolna increasingly hinge on rigorous, code-mixed-aware data analysis—and not just one kind. On one side, there is model and evaluation rigor: LLM benchmarking for post-call intelligence, ASR/WER evaluation, inter-rater reliability on human-labelled calls, and routing and latency economics. On the other, there is product and growth insight: understanding where self-serve users drop off in their journey, what patterns emerge across lakhs of monthly calls, and which use cases and configurations are actually working. Both currently sit with the Head of Product alongside strategy and roadmap ownership. We need a dedicated analyst to own the execution and recurring cadence across both-freeing product leadership to act on findings rather than produce them. What You’ll Do Model and Evaluation Analysis LLM and model benchmarking: Run structured comparisons across model providers such as Sarvam, DeepSeek, Gemini, and Claude variants for tasks including post-call extraction and LLM-as-judge scoring. Evaluate cost, accuracy, fill rate, and TTR, with particular attention to Hinglish and code-mixed content. Evaluation infrastructure: Build and maintain LLM-as-judge pipelines using tools such as DeepEval, design and track evaluation metrics, and run inter-rater reliability analysis such as Krippendorff’s alpha across human call reviewers. Golden dataset creation: Support the construction of golden datasets for ASR and transcript labelling, including flagging co