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Utilization Management Nurse Jobs

763 active opportunities · Updated for October 2026

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C
6mo ago

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. About the Role As a Software Engineer on the Model Routing & Inference team at SpaceXAI, you'll build the inference platform that powers every AI interaction in the product. This team owns the full inference path: making Cursor's AI faster, more reliable, and more cost-effective at a scale few teams in the world get to operate at. Every agent session, every tab completion, and every chat message flows through your stack. Example projects include... Building and evolving our inference gateway, a single abstraction over every provider's API semantics, so model onboarding becomes a config change. Designing intelligent cross-provider failover so no single provider outage causes user-visible degradation. Designing routing backpressure and admission control so traffic spikes don't cascade into providers. You may be a fit if You have deep experience building high-throughput, low-latency distributed systems, especially in inference serving, traffic routing, or real-time data pipelines. You're comfortable reasoning about cost/performance tradeoffs at scale (GPU utilization, provider economics, capacity planning). You have strong software engineering fundamentals and enjoy shipping pr

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Biohub
📍 Redwood City• Full-time• Hybrid• $241K – $331K/yr
6mo ago

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The AI Cluster Production Engineering team is part of the AI Compute Platform organization at Biohub, a non-profit research lab committed to open science and open-source AI. We own the design, operation, and reliability of large-scale multi-GPU AI clusters that power frontier AI biology research: protein language models, genomic foundation models, and scientific reasoning systems built to be shared, not monetized. Our clusters run Slurm on Kubernetes infrastructure and support everything from day-to-day AI researcher workflows to multi-node hero training runs at thousands of GPUs. The team works at the intersection of AI tooling, distributed systems, HPC, and frontier AI, debugging deep AI infrastructure problems and building AI systems critical to the entire AI organization. The Opportunity CZ Biohub's mission is to cure or prevent all human disease. Achieving that requires training frontier-scale AI biology models, and that demands reliable, high-performance compute infrastructure. This is production engineering work at a frontier AI lab, with the twist that the mission is biology and the science is open. You'll keep GPU clusters running at high utilization, debug the toughest distributed systems failures, and build the operational foundations for scaling to multi-thousand GPU hero runs. The technical problems are genuinely hard (e.g., multi-node distributed training, InfiniBand fabrics, large-scale storage, Slurm at scale) inside an organization where the work is aimed at helping peop

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About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. Responsibilities Lead and execute server, storage, data center, and networking motherboard design projects. Develop schematic diagrams, perform layout reviews, and maintain BOMs to ensure design quality. Conduct comprehensive power supply validation spreadsheet (Intel/AMD platforms), including efficiency, thermal, stress, dynamic load, ripple noise, stability, and regulation testing. Utilize VRTT / AMD validation tools and other industry-standard test platforms. Debug and resolve critical system issues, including burnout, EMI, acoustic noise, ESD, surge, and thermal challenges. Continuously optimize system performance across efficiency, thermal design, space utilization, noise, and cost dimensions. Requirement BS or MS in Electrical Engineering (or related field). 6+ years of hands-on design experience in VRM Core power, DDR power, and POL power on Intel/AMD platforms. Solid knowledge of power topologies (Buck, Boost, Hot-swap, etc.) and component-level tradeoffs. Strong expertise in power component specification, selection, and PCB layout best practices. Proficiency with industry tools such as OrCAD, PADS, Allegro, etc. Proven ability to diagnose and resolve complex hardware issues with a strong design problem-solving mindset. Effective communication and collaboration skills, with the ability to influence cross-functional

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OpenAI
📍 Singapore• Full-time• Remote
9mo ago

About the Team At OpenAI, our Trust, Safety & Risk Operations teams safeguard our products, users, and the company from abuse, fraud, scams, regulatory non-compliance, and other emerging risks. We operate at the intersection of operations, compliance, user trust, and safety working closely with Legal, Policy, Engineering, Product, Go-To-Market, and external partners to ensure our platforms are safe, compliant, and trusted by a diverse, global user base. The Global Safety Response Operations team provides 24/7 coverage for user safety, risk, and regulatory escalations across OpenAI’s products, handling the highest-priority cases that require human judgment and rapid response. The team operates as the core escalation and delivery arm of OpenAI’s safety operations, ensuring that our products remain safe and aligned with policy while enabling timely, empathetic, and consistent user support. About the Role The Global Safety Response Operations Lead is a hands-on team lead who both manages a regional Safety Response team and personally handles high-risk safety cases. This role combines frontline safety work with people leadership, operational ownership, and cross-functional coordination. You will lead a team of Safety Response Analysts who handle OpenAI’s most sensitive and high-impact cases, while also personally contributing to casework for complex, high-risk, or high-visibility issues. You will own the execution of high severity escalations in your region and ensure proper execution and communication to cross functional stakeholders You will be accountable for ensuring your region consistently meets utilization, quality, and SLA targets while serving as the operational interface with Product, Policy, Legal, Investigations, and regional stakeholders. This is a 24/7 global operation that requires flexibility to support rotating shifts, including nights, weekends, and holidays, as part of a leadership on-call model. In This Role, You Will: Lead and coach a regional te

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Palantir
📍 United States• Full-time• Hybrid• $110K – $150K/yr
10mo ago

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 Platform Intelligence Engineers are the engine behind Palantir’s most strategic and important operations. Engineers are responsible for designing, creating, and maintaining the critical data infrastructure layer that powers decision-making across the business. This infrastructure enables teams to understand product usage, stability trends, cost efficiency, value creation, revenue streams, and more. As an Intelligence Engineer, you will partner with teammates and leaders across the business to address, measure, and evaluate Palantir’s internal strategic and tactical performance. You will keep business outcomes in mind as you develop data pipelines, perform analysis, and work with stakeholders to operationalize insights that propel the business forward. Depending on which team you join, you might analyze cloud utilization, user metrics, stability KPIs, cost optimizations, or even model pricing changes all while ensuring best in class support for our partner teams. You will use Palantir’s platforms, just as Palantir’s customers do, to clean and enrich troves of data from disparate sources, allowing you to unlock key insights, create visualizations and custom applications that help drive day-to-day outcomes. Teams across Palantir will consult with and rely on you to help guide planning and decision-making for a wide range of topics while balancing various sets of priorities and weighing costs. About You You are proficient in Python and have experience in a previous or current job writing code on a day-to-day basis. You understand the challenges of finding the right data to answer a problem, cleaning data, and then distilling findings to executive-leve

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Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity Postman is seeking an experienced AI Systems Reliability Engineer to help define, build, and maintain the infrastructure and processes that ensure the reliability, scalability, and performance of Postman’s AI-powered API and agentic systems in production. This role focuses on monitoring, availability, incident response, and automation to support AI services and tools trusted by millions of developers globally. What You’ll Do Develop and manage reliability metrics (SLOs) for AI-driven API services and agentic AI platform features Implement comprehensive observability and monitoring systems for real-time performance and fault detection Design and drive automated failover, recovery, and incident response strategies for high-availability AI infrastructure Optimize resource utilization, particularly GPU/accelerator efficiency, ensuring cost-effective AI system operation Collaborate closely with engineering, platform, and product teams to align reliability efforts with broader organizational goals Lead efforts to build internal tooling and automation focused on AI system stability and operational excellence Drive continuo

aigorust
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EA
EnCharge AI
📍 India• Full-time
15mo ago

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML workloads. You will collaborate with hardware architects, and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge’s Inference Accelerators. Responsibilities Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization. Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges. Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations. Develop compiler optimizations and passes that convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR). Implement parsing, semantic analysis, and IR generation for deep learning frameworks. Research and integrate the latest advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers. Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations. Qual

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C
Cohere
📍 Toronto• Full-time• Remote• C$250K – C$535K/yr
16mo ago

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Machine Learning Engineer specializing in pretraining data, you will play a pivotal role in developing the data pipeline that underpins Cohere’s advanced language models. In this role, you will conduct data ablations to evaluate data quality and construct pre-training data mixtures to enhance model performance. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role between EST and EU. Key Responsibilities: Conduct data ablations t

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OpenAI
📍 San Francisco• Full-time• $295K – $555K/yr
17mo ago

About the Team OpenAI’s Inference team powers the deployment of our most advanced models - including our GPT models, 4o Image Generation, and Whisper - across a variety of platforms. Our work ensures these models are available, performant, and scalable in production, and we partner closely with Research to bring the next generation of models into the world. We're a small, fast-moving team of engineers focused on delivering a world-class developer experience while pushing the boundaries of what AI can do. We’re expanding into multimodal inference, building the infrastructure needed to serve models that handle image, audio, and other non-text modalities. These workloads are inherently more heterogeneous and experimental, involving diverse model sizes and interactions, more complex input/output formats, and tighter coordination with product and research. About the Role We’re looking for a software engineer to help us serve OpenAI’s multimodal models at scale. You’ll be part of a small team responsible for building reliable, high-performance infrastructure for serving real-time audio, image, and other MM workloads in production. This work is inherently cross-functional: you’ll collaborate directly with researchers training these models and with product teams defining new modalities of interaction. You'll build and optimize the systems that let users generate speech, understand images, and interact with models in ways far beyond text. In this role, you will: Design and implement inference infrastructure for large-scale multimodal models. Optimize systems for high-throughput, low-latency delivery of image and audio inputs and outputs. Enable experimental research workflows to transition into reliable production services. Collaborate closely with researchers, infra teams, and product engineers to deploy state-of-the-art capabilities. Contribute to system-level improvements including GPU utilization, tensor parallelism, and hardware abstraction layers. You might thrive in t

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About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Hybrid at our office in Amsterdam or Remote in the UK. Responsibilites Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinkin

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AC
18mo ago

Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you’ll be part of a passionate team dedicated to accomplishing hard things, together. Principal Consultant Location: Chennai, India | Work Model: In Office Our Customer Success team in Chennai serves as elite technical advisors for global enterprise teams. We bridge deep software architecture with business strategy, building scalable platform environments that leverage AI-Powered Process Automation to solve mission-critical operational challenges. As a Principal Technical Consultant , you will assume architectural leadership for multi-application platform design, execution, and performance optimization. Top engineering talent joins Appian in this role to move beyond basic application maintenance and ensure applications are resilient, scalable, and built to power mission-critical operations at enterprise scale . What You’ll Do Architect Platform Scalability: Build and maintain standards and tools to ensure high performance and resilience with a focus on reusability, schema optimization, data modeling , system performance, and responsive UX/UI . Engineered Integrations: Perform hands-on design, development, and code reviews using SQL views , stored procedures , and high-concurrency REST/SOAP web services/APIs . System-Level Troubleshooting: Rapidly isolate performance bottlenecks, memory leaks, resource contention, and latency spikes across the entire web application stack. Performance Analysis & Profiling: Analyze database execution plans, JVM/memory utilization, and Locust load test outputs to resolve root-cause architectural bottlenecks. Technical Communication & Enablement: Translate complex system diagnostics in

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C
Cohere
📍 London• Full-time• Remote• £250K – £535K/yr
20mo ago

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Performance Engineer in the Pre-Training team you will be responsible for optimizing the performance of our advanced language models and systems. Their primary focus is on improving key model training metrics, such as training throughput, ensuring high accelerator utilization. The team combines expertise in software engineering, machine learning, and low-level kernel design and development to design robust systems and enhance model performance. You will work on identifying and removing performance bottlenecks, develop cutting-edge training and profiling tools to help Cohere's mission of providing efficient and reliable language understanding and generation capabilities and drive innovation in the field of natural language processing. Note: We have offices in London, Toronto, New York and San Francisco, but we’re also remote-friendly! This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration. Key Responsibilities: Design and write high-performant and scalable software for training. Understand architectural modific

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About SAI Group SAI Group is a private investment firm dedicated to incubating and scaling AI-powered enterprise software companies. Our portfolio spans across rapidly growing businesses that serve over 2,000 global customers, generating nearly $600 million in annual revenue and employing over 4,000 individuals worldwide. As we continue to scale, we are focused on building world-class teams to drive our portfolio companies' success. Role Overview: As a Research Engineer, you will be instrumental in exploring and establishing best practices for leveraging and extending novel Generative AI based technologies to develop groundbreaking solutions for enterprise use cases. This role offers a unique opportunity to delve into the rapidly evolving world of foundation models, AI agents, reasoning models etc. and contribute to the design and development of an innovative enterprise AI platform to deliver transformative, AI-enabled work experiences for enterprise users. What You Will Do Experimentation and Research : Systematically explore various technologies and strategies such as foundation models, agentic workflows, ontology and knowledge graphs, reinforcement learning, dynamic prompting, retrieval augmented generation, and collaborative problem solving to enhance our understanding and utilization of foundation models and related Generative AI frameworks. You will design and conduct experiments to probe the limits and capabilities of different foundation models, frameworks and their application strategies. Development and Analysis : Design experiments to understand the capabilities and limits of foundation models. Build tools necessary for conducting experiments, run these experiments, and meticulously analyze the results. Build on the quantitative and qualitative findings from these experiments to design future experiments and shape the architecture of our enterprise AGI platform. Prototyping and Innovation : Take charge of developing and

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OpenAI
📍 San Francisco• Full-time• Remote• $255K – $445K/yr
Just now

About the team The Browser Use team builds the technology that enables agents to interact with browsers across our products. Our work spans infrastructure, tooling, and user experiences, both on users’ devices and in the cloud. We partner with research to improve our models’ browser-use capabilities and with web standards bodies to shape how agents interact with the web. Our products include ChatGPT for Chrome, the ChatGPT in-app browser, and the cloud computer used in dots and ChatGPT Work. We see the browser as a universal connector. If we can enable our models to use it effectively, they can do anything. Come help us build the future of browsing! About the role We’re looking for a product-oriented engineer to build and scale our cloud computer infrastructure. Our goal is to give every one of our users access to an agent with their own computer in the cloud. Build novel solutions to problems like authentication, user takeover, and enterprise network access. You’ll help own the systems that provision, run, and manage the environments our agents use, making them reliable, responsive, and efficient as demand grows. This role combines infrastructure depth with close attention to the user experience. You’ll partner with research and engineering teams to bring new computer-use capabilities into production, working across container orchestration, backend services, and product experiences. In this role you will Build and scale infrastructure for running agent-controlled browsers and computers in the cloud. Develop services for provisioning environments, managing sessions, and coordinating their lifecycle. Improve reliability, performance, resource utilization, and observability across the fleet. Diagnose issues across Linux, containers, networking, and browser execution. Build APIs and tooling that make cloud computers easy for research and product teams to use. Work closely with research to understand emerging requirements and improve how computer use works. Develop auth

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C
Cursor
📍 United States• Full-time• Remote
Just now

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. About the role The User Operations team owns the support experience for Cursor's users - from individual developers to our largest enterprise accounts. As we've scaled across regions, the volume and richness of our support data has grown faster than our ability to make sense of it. We're looking for a Data Analyst to change that. This role sits inside our Product and Engineering organization with a dotted line to the Head of User Operations and owns the data and reporting layer for Support. You'll turn ticket data, SLA performance, customer sentiment, and product signal into the dashboards and analysis that leadership uses to run the org - and into the evidence Product and Engineering use to decide what to fix next. Support is one of the clearest signals we have about where the product is working and where it isn't. Your job is to make that signal legible. What you'll do Build and own the reporting layer for Support: ticket volume, SLA attainment, resolution times, help center performance, CSAT/CES/sentiment, and capacity utilization across regions and tiers Partner with Support leadership to turn open questions - "are we getting faster but less accurate?", "where is enterprise

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