Utilization Management Nurse Jobs

About the Team ChatGPT relies on a large and growing GPU fleet to serve inference workloads reliably and efficiently. Our team builds the software, tooling, and operational systems that help manage this fleet at scale. We work across production engineering, distributed systems, capacity management, and operational automation to improve reliability, reduce manual work, and make better use of available compute. About the Role We are looking for a software engineer with experience building or operating large-scale production systems. You will develop the systems that help manage the GPU fleet powering ChatGPT, including tooling for fleet health, capacity planning, operational automation, and incident response. You will work closely with infrastructure, research, and product engineering teams to improve reliability, developer productivity, and compute utilization. This role is a good fit for engineers who enjoy solving complex operational problems and building software that makes production infrastructure easier to run at scale. In This Role, You Will Build software and internal tools to manage large-scale GPU infrastructure supporting ChatGPT inference. Develop systems for capacity planning, fleet health monitoring, and resource utilization. Automate operational workflows, including incident detection, diagnosis, and response. Identify and address bottlenecks affecting fleet reliability, scalability, and performance. Partner with infrastructure, research, and product engineering teams to improve the compute platform. You Might Thrive in This Role If You Have experience operating large-scale production infrastructure, GPU clusters, or other compute-intensive distributed systems. Have a background in production engineering, site reliability engineering, infrastructure engineering, or platform engineering. Have built software that automates operational workflows and reduces manual work. Have worked with distributed infrastructure, cluster orchestration, or large-scale int

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Job Description/ Responsibilities: Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production. Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow. Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data Technology Eva

About Us What if your work could drive change in a globally established industry, shaping processes that touch every corner of the world? At Forto, we are at the forefront of change, harnessing the power of AI to revolutionise logistics. We want to reinvent digital supply chains to be transparent, frictionless and sustainable. From day one, our mission has been to simplify global trade – creating a seamless and efficient logistics process. Your role & Mission As a Senior Backend Engineer in our Shipment team, you will build the "brain" behind our logistics operations. You’ll maintain and evolve a sophisticated event-driven architecture designed to answer one crucial question: "How do we move this shipment most efficiently?" From contract rate management to automated shipment nomination, you will lead the charge in creating reliable, data-heavy systems that optimize our global portfolio. You aren’t just writing code; you’re building a revenue-driving engine. Working alongside industry experts, you will mentor your team to deliver robust services that enable NVOCCs to thrive. If you are passionate about leading teams to solve massive logistical challenges, we want to hear from you. What you will do Design and implement robust backend services for capturing, storing, and validating procurement contract rates and allotment volumes, ensuring 100% data integrity for our supply chain logic. Lead the evolution of our event-driven microservices to process high-velocity data, enabling real-time updates on contract utilization and space availability. Refactor and optimize existing systems responsible for shipment-to-contract matching to ensure low-latency performance and high maintainability. Build and iterate on the logic that answers "Which contract should we use?" by automating the nomination process based on cost, volume commitments, and carrier performance. Streamline the ingestion and management of complex carrier agreements, moving from manual entry toward a fully a

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Through a combination of strategic partnerships and self-built campuses, we are scaling the compute, storage, and networking platforms that power frontier AI training and inference. The Scaling Analytics team builds the data and software systems that help Industrial Compute understand, plan, and operate infrastructure at global scale. We work across capacity, hardware, storage, infrastructure software, and operational systems to connect fragmented sources of infrastructure data and make that information reliable and usable for engineering and planning. As OpenAI's infrastructure footprint grows, CPU and storage data increasingly spans internal platforms, vendor systems, APIs, databases, object storage, capacity management systems, and operational tooling. Building reliable connections across these environments is critical to understanding available capacity, utilization, fleet state, and infrastructure growth. About the Role We are seeking a Data Engineer to build the data systems and integrations that connect OpenAI's CPU, storage, and supporting infrastructure platforms. This role sits at the intersection of data engineering and backend software engineering. Rather than focusing primarily on traditional analytical pipelines, you will build the software and integrations required to collect, normalize, and make infrastructure data available across a heterogeneous set of systems. CPU and storage data may originate from internal infrastructure platforms, vendor APIs, databases, object storage, capacity systems, and operational services. You will determine how to reliably connect these systems and where those integrations should live—whether within an existing infrastructure service, an orchestration framework, a scheduled workload, or a purpose-built application. You will work closely with Infrastructure Engineering, Capacity Engineering, Storage,

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last-mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role You will be a valuable and developing member of the Service Operations team at DoorDash Labs. You will build on your existing technical skills to perform diagnostic, maintenance, and repair work to keep our robot fleet and electric bicycles operating at peak performance, supporting our fleet utilization goals. You will work closely with Senior Service Technicians and your manager to expand your troubleshooting skills, gain deeper familiarity with our systems, and progressively take on more complex repairs. This is an on-site role with expectations of 100% in-office presence in Mesa, AZ. This position is available on the AM shift (7:00 AM – 3:30 PM), five days per week, including at least one weekend day. You’re excited about this opportunity because you will… Perform standard and intermediate Service Technician tasks with growing independence, including service and upkeep of robotic systems and electric bicycles. Repair common faults in robotic platforms, modular components, electric bicycle drivetrains, and support vehicles using established troubleshooting procedures. Assist with complex or unusual faults alongside senior or lead technicians to learn advanced diagnostic methods for both robotic systems and e-bikes. Complete repairs on electrical systems, control units, battery packs, and hardware under guidance, with opportunities to develop toward independent advanced repairs. Use and interpret technical manuals, schematics, and diagnostic flowcharts to guide your work, applying these resources to both robot and electric bicycle service tasks. Document all diagnostic steps, repair actions, and component failures in the service management system to maintain accurate rec

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

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

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Position Description: This is a key leadership role in the Professional Services (Technical Architecture) organization, responsible for the implementation of Okta services. The Senior Manager is an experienced, enthusiastic, and hands-on leader preferably in the Security and/or Identity & Access Management domain, who can rapidly learn and apply the Auth0 value proposition to customers of all sizes. The Senior Manager is a leader of a high-performing team of Technical Architects, functioning in a "player-coach" model. This role requires impressive field and management experience and involves mentoring the team of Technical Architects. You have experience managing a technical team, resource forecasting, change & escalation management and operational excellence for Professional Service teams. You have a deep understanding of reporting and metrics as well as capacity planning and utilization targets. You will have a strong Consulting background with an ability to handle multiple work streams and be deeply comfortable with client issues and resolutions. Key Responsibilities Team Leadership: Hiring, growing, and retaining a team of Professional Service Technical Architects. Providing direct management, mentoring, and support to ensure their continued technical, professional, and career growth. Up-skilling team members to ensure they have the expertise to successfully deliver Okta to customers. Manages outlined objective and subjective performance m

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

About the Team API Multicloud partners with cloud service providers (CSPs) to bring OpenAI’s frontier models and APIs into the cloud environments where developers and enterprises already build. We own the API end to end across CSP platforms, from API integration and request routing through inference execution, capacity management, and day-to-day operations. Our mission is to make these capabilities available broadly and safely while preserving the reliability and developer experience customers expect from OpenAI. Delivering that experience requires work across the stack: adapting API services and cloud-native integrations, bringing up model-serving environments, validating new releases, and operating the systems that connect customer requests to available capacity. We work directly with CSP engineering teams and partner closely with OpenAI’s inference, API, infrastructure, security, and Safety Systems teams. Together, we turn new model capabilities and partner requirements into dependable production services, with attention to performance, operational readiness, and efficient use of compute. Our work contributes to OpenAI’s AWS partnership , including the launch of Daybreak Red and Daybreak Blue on Amazon Bedrock . We’re building on that foundation to bring OpenAI’s API to additional CSPs. These efforts let customers use OpenAI capabilities within the cloud infrastructure, security controls, and workflows they already rely on. About the Role We’re looking for experienced infrastructure engineers to design, build, and operate the systems that run OpenAI’s API across CSP platforms. You’ll help establish the cloud deployment platform: configuring and launching model-serving environments, planning capacity, improving caching and utilization, and making new releases safe and repeatable. Working closely with inference engineers, you’ll connect advances in model serving to the infrastructure and operational practices needed to run them reliably in production. The role call

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last-mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role You will be a valuable and developing member of the Service Operations team at DoorDash Labs. You will build on your existing technical skills to perform diagnostic, maintenance, and repair work to keep our robot fleet and electric bicycles operating at peak performance, supporting our fleet utilization goals. You will work closely with Senior Service Technicians and your manager to expand your troubleshooting skills, gain deeper familiarity with our systems, and progressively take on more complex repairs. This is an on-site role with expectations of 100% in-office presence in Fremont, CA, San Jose, CA, or Sunnyvale, CA. You’re excited about this opportunity because you will… Perform standard and intermediate Service Technician tasks with growing independence, including service and upkeep of robotic systems and electric bicycles. Repair common faults in robotic platforms, modular components, electric bicycle drivetrains, and support vehicles using established troubleshooting procedures. Assist with complex or unusual faults alongside senior or lead technicians to learn advanced diagnostic methods for both robotic systems and e-bikes. Complete repairs on electrical systems, control units, battery packs, and hardware under guidance, with opportunities to develop toward independent advanced repairs. Use and interpret technical manuals, schematics, and diagnostic flowcharts to guide your work, applying these resources to both robot and electric bicycle service tasks. Document all diagnostic steps, repair actions, and component failures in the service management system to maintain accurate records and support fleet readiness. Learn from and collaborate with experienced technicians,

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last-mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role You will be a fundamental and experienced member of the Service Operations team at DoorDash Labs. You will complete more advanced diagnostic and repair work to maximize uptime, supporting our overall fleet utilization goals. You will report to the Associate Operations Manager, Service, in our DoorDash Labs organization. This is an on-site role with expectations of 100% in-office in Fremont, CA, San Jose, CA, or Sunnyvale, CA. You’re excited about this opportunity because you will… Execute any Senior Service Technician task and: Diagnose complex, intermittent, or unusual faults in robotic systems, modular components, and support vehicles, often requiring advanced troubleshooting techniques and interpretation of complex data Perform advanced repairs, including component-level troubleshooting and fixes on intricate electrical systems, control units, and associated hardware, with minimal supervision Interpret complex technical manuals, schematics, and diagnostic flowcharts to guide troubleshooting efforts Meticulously document complex diagnostic processes, root cause hypotheses, non-standard troubleshooting steps, repair details, and component failure information in the service management system, contributing potential updates to the knowledge base Provide technical guidance, mentorship, and on-the-job assistance to Level 2 Technicians for challenging tasks Work independently to manage and prioritize assigned workload effectively Calibrates, configures, and maintains specialized diagnostic tools and test equipment We operate 7 days a week, 16 hrs a day to support Robot Operations. During training, you will be on a temporary schedule until your on-the-job training is completed

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last-mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role You will be a valuable and developing member of the Service Operations team at DoorDash Labs. You will build on your existing technical skills to perform diagnostic, maintenance, and repair work to keep our robot fleet and electric bicycles operating at peak performance, supporting our fleet utilization goals. You will work closely with Senior Service Technicians and your manager to expand your troubleshooting skills, gain deeper familiarity with our systems, and progressively take on more complex repairs. This is an on-site role with expectations of 100% in-office presence in Fremont, CA, San Jose, CA, or Sunnyvale, CA. You’re excited about this opportunity because you will… Perform standard and intermediate Service Technician tasks with growing independence, including service and upkeep of robotic systems and electric bicycles. Repair common faults in robotic platforms, modular components, electric bicycle drivetrains, and support vehicles using established troubleshooting procedures. Assist with complex or unusual faults alongside senior or lead technicians to learn advanced diagnostic methods for both robotic systems and e-bikes. Complete repairs on electrical systems, control units, battery packs, and hardware under guidance, with opportunities to develop toward independent advanced repairs. Use and interpret technical manuals, schematics, and diagnostic flowcharts to guide your work, applying these resources to both robot and electric bicycle service tasks. Document all diagnostic steps, repair actions, and component failures in the service management system to maintain accurate records and support fleet readiness. Learn from and collaborate with experienced technicians,

We are looking to speak to candidates who are based in Seoul for our hybrid working model. About the role MongoDB Engagement Managers are quota-carrying Professional Services Sales roles. Engagement managers utilize customer-facing sales, technical, consulting, and commercial experience to scope, negotiate and close Professional Services opportunities to accelerate and de-risk the adoption of MongoDB by our customers. As an Engagement Manager, you will be a key leader within the PS team and work cross-functionally with the Sales, Professional Services, and Customer Success organizations to drive professional services sales. Here are a few informative blogs about the Engagement Management role: https://www.mongodb.com/blog/post/engagement-management-mongodb-meet-lalitesh-pal https://www.mongodb.com/blog/post/how-engagement-managers-help-customers-succeed What you will be doing Understand customers’ overall portfolio of applications and datasets, IT and business priorities and success measures to adapt, develop and design specific digital transformation approaches involving MongoDB technologies Help transform companies by translating their use-cases, pains, and needs into scoped projects and statements of work Partner with a best-in-class sales organization and work effectively as a part of a larger team to develop account strategies and plans for the successful adoption, growth, and utilization of MongoDB Have a solid sense of ownership, driving all deals or technical scopings from inception to closure Manage the Professional Services pipeline for bookings and revenue forecasts for your region Expertly articulate the business value of professional services, talking knowledgeably and credibly about service delivery issues, challenges, strategies, approaches, and mitigating risks Work with our practice team to propagate internal skills and experience through the development of repeatable assets (estimates, proposals, SOWs, templates, tools, case studies etc.) Wor

We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters. Responsibilities Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads Manage and optimize Slurm-based HPC environments for distributed training of large language models Develop robust APIs and orchestration systems for both training pipelines and inference services Implement resource scheduling and job management systems across heterogeneous compute environments Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands Qualifications Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization Experience with deploying and managing distributed training systems at scale Deep understanding of container orchestration and distributed systems architecture High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies) Experience managing GPU clusters and optimizing compute resource utilization Required Skills Expert-level Kubernetes administration and YAML configuration management Proficiency with Slurm job scheduling, resource mana