Runpod is looking for a Director of Security to lead security strategy, compliance, secure development, incident response, and security operations.
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Runpod is looking for a Director of Security to lead security strategy, compliance, secure development, incident response, and security operations.
Location: Remote - US Role Overview This is a senior individual contributor role with significant architectural ownership. You will set the technical direction for how Backblaze detects, correlates, and responds to infrastructure incidents across our data centers, and you will mentor other engineers on the team as that platform matures. If you have a passion for making complex distributed systems visible, you are comfortable making architecture decisions that will outlive your tenure, and you are excited about applying AI and agentic automation to infrastructure operations, this role was built for you.. Key Responsibilities Technical Leadership Set technical direction and standards for observability across the organization, including instrumentation conventions, alerting philosophy, and dashboard design patterns. Mentor engineers on the Observability team and act as a technical resource for SRE, Storage Engineering, and Network Engineering on observability practice. Lead design reviews for observability work and represent the team in cross-functional architecture discussions. Evaluate build-versus-buy decisions for observability and AIOps tooling, including data sovereignty and compliance considerations. Produce and maintain design documentation, runbooks, and architectural decision records that make the platform operable and extensible by future contributors. Observability Platform Own and evolve our metrics pipeline, including VictoriaMetrics, Prometheus, and the Consul-based service discovery layer that keeps scrape targets current as infrastructure scales. Own and expand our logging stack (OpenSearch, Logstash, and Filebeat) across all Backblaze data centers. Architect and expand distributed tracing with Jaeger and OpenTelemetry, extending coverage beyond the current application instrumentation to new services. Define and maintain Grafana dashboard standards for infrastructure, storage, and application performance visibility. Drive expansion of internal application telemetry in partnership with application teams to improve visibility. Define capacity and retention strategy for the telemetry stack as the fleet grows. Infrastructure & Automation Own infrastructure-as-code for observability stack deployments across multiple Kubernetes clusters. Write and review automated playbooks for configuration management and automation across Debian-based bare metal servers. Partner with the SRE team on Consul-based service discovery for VictoriaMetrics scrape target automation. Lead Ceph storage observability, including OSD health, performance metrics, and integration with alerting. Collaborate with the Network Engineering team on BGP, routing, and network-level observability. Required Qualifications 8+ years in a systems engineering, SRE, DevOps, or observability-focused role, including demonstrated technical leadership on a platform or infrastructure team. Deep hands-on experience with Prometheus, VictoriaMetrics, or equivalent metrics platforms, including PromQL, Alertmanager, and operating these systems at scale. Experience designing and operating log aggregation pipelines such as Elasticsearch/OpenSearch, Logstash, Filebeat, or similar. Working knowledge of distributed tracing (Jaeger, OpenTelemetry, or equivalent), including instrumentation strategy, not just operation. Proficiency in Python and/or Go for automation and tooling. Experience with Kubernetes, including deploying workloads and understanding pod networking and storage. Experience with infrastructure-as-code tooling and configuration management. Strong understanding of Linux internals, with Debian/Ubuntu preferred. Demonstrated experience mentoring engineers and raising the technical bar on a team. Excellent written and verbal communication skills. You'll work across engineering, SRE, security, and leadership, and you'll be expected to write design documents that drive decisions. Preferred Qualifications Experience leading the evaluation or deployment of AIOps tooling, including alert correlation, deduplication, or automated root cause analysis. Experience building, deploying, or operating AI agents or agentic AI systems. This is a strong differentiator. Familiarity with LLM APIs (Anthropic, OpenAI) or self-hosted LLM inference in an infrastructure context. Familiarity with Ceph storage, including OSD management, pool configuration, and CRUSH maps. Experience with incident management platforms. Familiarity with BGP, network observability, or working in multi-DC environments. Experience with secrets management in production environments. Experience operating in a regulated or compliance-driven environment. Prior experience in a storage-focused company or hyperscale infrastructure environment. What You'll Work On A telemetry stack spanning several data centers with exabytes of storage under observation. Real infrastructure at scale: Kubernetes, Ceph, Vitess, KVM, and a custom storage platform serving hundreds of thousands of customers. A collaborative team that values engineering excellence, transparency, and operational rigor. Pay Transparency To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. Final offer amounts are determined by multiple factors including candidate location, skills, depth of work experience, and relevant licenses/credentials. The expected salary range for this role is $178,000 - $200,000 plus 10% target annual bonus and RSUs. At Backblaze, we value being fair and good to our customers, partners, and employees. Diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We are proud to be an Equal Opportunity Employer.
Location: Lisbon; Portugal Workplace: Hybrid ROLE HIGHLIGHTS: - Role: Forward Deployed AI Engineer - Department: Forward Deployed Engineering - Location: Portugal (Lisbon) - Reports to: VP, Forward Deployed Engineering - Working type: Hybrid (On-site at customer locations approx. 50% of time) - Must be eligible and able to attain relevant national and NATO security clearances. - Must be based in-country and native level speaker of the country you're deploying to. THE MISSION OF THE FORWARD DEPLOYED AI ENGINEER In this role, you'll be the hands-on AI builder defense and intelligence customers rely on. You’ll deploy ICEYE’s intelligence platform into secure (often air-gapped) environments and rapidly ship AI-powered workflows on top of it—everything from Docker-based deployments to RAG systems fusing SAR imagery with intelligence reports. This is a ship-code-daily role: turning raw satellite data into mission-critical tools analysts use to protect nations. WHO WE ARE ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. DAY TO DAY RESPONSIBILITIES: PLATFORM DEPLOYMENT & INTEGRATION - Deploy ICEYE's intelligence platform into customer secure environments (on-premise, air-gapped networks, classified data centers). - Build and maintain containerized applications (Docker) and manage deployments in customer Kubernetes clusters. - Develop APIs and data pipelines connecting ICEYE systems to customer C4ISR infrastructure and intelligence tools. - Troubleshoot deployment issues in disconnected environments without external internet access. AI SOLUTION DEVELOPMENT & CUSTOMIZATION - Build Retrieval-Augmented Generation (RAG) systems that combine ICEYE SAR data with customer intelligence documents for context-aware analysis. - Develop AI agents and workflows using frameworks like LangChain, LangGraph, or similar tools to automate analytical tasks. - Implement prompt engineering strategies and conversational AI interfaces that enable analysts to query satellite data using natural language. - Create Model Context Protocol (MCP) integrations connecting AI systems with customer data sources. DATA FUSION & INTELLIGENCE WORKFLOWS - Build data fusion pipelines combining SAR imagery with additional intelligence sources (AIS, RF signals, optical imagery, SIGINT). - Develop automated workflows that correlate and cross-reference information across different data modalities. - Create lightweight tools, dashboards, and alerting systems tailored to customer operational needs. CUSTOMER ENGAGEMENT & RAPID PROTOTYPING - Work embedded with intelligence analysts, data scientists, and military operators to understand mission-critical problems. - Rapidly prototype AI-powered solutions (code first, polish later) that address immediate operational requirements. - Conduct hands-on training sessions on platform capabilities and AI workflow usage. - Gather customer feedback and translate it into technical requirements for ICEYE's product and engineering teams. WHAT WE ARE LOOKING FOR MUST HAVE SKILLS: - 3+ years hands-on software engineering building and deploying production systems. - Strong Python programming skills (required) plus one of: Go, TypeScript, or Rust. - Hands-on experience with LLMs, prompt engineering, and RAG systems. - Working knowledge of agent frameworks (LangChain, LangGraph, pydantic-ai) and vector databases. - Experience with Docker and deploying in secure / isolated / air-gapped environments. - Practical experience with APIs, data pipelines, and integrating systems in production, - Familiarity with Linux and basic Kubernetes operations. - Builder mindset: ship fast, iterate with feedback, and prioritize working solutions over perfect architecture. - Strong communication + customer engagement, able to work embedded with intelligence analysts / military operators. - Strong spoken and written English, able to explain technical concepts to non-technical stakeholders. - Willingness to travel 40–60% to customer sites within the region. NICE TO HAVE SKILLS: - Experience in defense, intelligence, or government operational environments. - Deploying to on-prem data centers and/or air-gapped networks. - Familiarity with geospatial data, satellite imagery, or remote sensing. - Experience with MCP integrations, multi-agent systems, or agentic workflows. - Deeper Kubernetes, IaC (Terraform/Ansible), and/or offline CI/CD. - Understanding of intelligence analysis workflows and defense/government requirements. - Experience with data fusion, multi-source intelligence integration, or GIS tools (ArcGIS, QGIS). - Background in solution engineering, technical consulting, or customer success. - Experience in defense tech (e.g., Palantir, Anduril, Scale AI, similar startups). APPLICATION PROCESS - Talent Acquisition Interview - Take home task - Hiring Manager Interview - Hiring Team Interview - Offer Decision WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing—at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. OUR COMMITMENT TO DIVERSITY, EQUITY AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com https://www.iceye.com
Nscale is looking for a Senior Network Engineer Deployment to deploy and validate networks for GPU clusters across Europe.
Location: Remote Workplace: Remote Phantom https://phantom.com is on a mission to connect the world to the freedom of open markets. Tens of millions of people all over the world use Phantom to access global markets that never close, including perpetuals, prediction markets, tokenized assets, stablecoins and memes. Phantom users are able to discover the markets that matter and the cultural moments that shape them, building conviction through real-time data and the verified performance of top traders. With self-custody and access to open networks at its core, Phantom lets them control their financial moves in the same app they use to safely store or spend money worldwide. Phantom has reached #1 in Google Play's finance category and consistently ranks in the top 50 apps across all categories. Check out our Forbes Fintech 50 https://www.forbes.com/sites/ninabambysheva/2026/02/23/inside-phantoms-battle-plan-to-win-the-crypto-fueled-superapp-war/ and CNBC and Statista's World's Top Fintech Companies 2026 https://www.cnbc.com/worlds-top-fintech-companies-2026/! We are around 180 people, fully remote, backed by a $150M Series C investment from a16z, Sequoia Capital and Paradigm. RESPONSIBILITIES - Kubernetes Ownership: Manage and scale Kubernetes clusters on AWS EKS, ensuring reliability, performance, and security. - Infrastructure Automation: Implement and maintain Infrastructure-as-Code (Terraform/Pulumi) to automate infrastructure provisioning and management. - Performance Optimization: Monitor and optimize system performance, scalability, and resource utilization. - Blockchain Infrastructure: Configure and maintain crypto nodes across multiple blockchains to support our wallet’s operations. - Database Scaling: Optimize and scale database infrastructure to handle terabytes of blockchain data efficiently. - System Reliability: Continuously improve system uptime, monitoring, and observability using tools like Datadog and OpenTelemetry. - Collaboration: Work closely with backend and product teams to support feature development and system scaling. QUALIFICATIONS - 5+ years in a SRE or Software Engineer role. - Strong hands-on experience with Kubernetes (EKS) in production environments. - Proficiency with AWS infrastructure and services (EC2, S3, RDS, IAM). - Solid experience with Docker and Infrastructure-as-Code tools like Terraform or Pulumi. - Monitoring and observability experience using tools like Datadog or OpenTelemetry. The target base salary for this role will range between $200,000 to $250,000 with the addition of equity and benefits. This is determined by a few factors including your skillset, prior relevant experience, quality of interviews and market factors (such as location) at the point in time of offer. Why Work With Us Phantom's journey to becoming a global trading app began with making crypto easier to use. Today, we’re building on that foundation to help people discover the markets that matter, make informed financial moves, and safely store or spend their money worldwide. Joining Phantom means helping shape that next chapter: building products that bring the freedom of open markets to more people. - Build for global impact: Create products used by tens of millions of people, making innovative financial markets more accessible to users around the world. - Make complexity feel simple: Solve meaningful challenges across design, engineering, and user experience to make discovering markets and managing money seamless. - Put users in control: Help build a future where people have greater freedom over their assets and financial decisions, with security and self-custody at the foundation. Benefits (only available to full-time employees) - Competitive salary and equity - Comprehensive insurance (medical/dental/vision): base plan 100% covered - Flexible hours and a long-standing, supportive remote environment - Unlimited vacation: Take time when you need it (and we really mean it!) - 401(k) retirement plan - Wellness stipend - Weekly meal stipend - Learning & Development stipend - Remote / WFH set-up stipend We strongly encourage candidates of all backgrounds to apply. We believe that our work is stronger with a variety of perspectives, and we’re eager to further diversify our company. If you have a background that you feel would make an impact at Phantom, please consider applying. We’re committed to building an inclusive, supportive place for you to do the best work of your career. By submitting your resume and application materials, you acknowledge and agree that Phantom Technologies, Inc. ("Phantom") collects and processes your personal information (including application materials, interview records, and related data) to evaluate your candidacy. Phantom may use AI-powered tools and third-party service providers for transcription, note-taking, scheduling, and other administrative tasks. Phantom does not sell your information and your materials will be handled securely and in accordance with applicable data protection laws.
Location: Bulgaria Company Background Our client is a travel technology company developing cloud-native, AI-powered software for airlines and hospitality brands. Its products help customers improve commercial performance, reduce costs, and evolve their digital commerce capabilities. The company’s technology is designed to work alongside existing airline systems, allowing customers to introduce new capabilities without replacing their current technology landscape. Project Description You will contribute to a large-scale greenfield travel-technology initiative supporting the launch of a new airline operation. The project uses a modern commercial platform to enable flexible retailing, pricing, and digital shopping experiences across travel products and ancillary services. Technologies GCP, AWS Wiz Cloudflare WAF, Bot Management, DNS, TLS, DDoS Protection and Rate Limiting Terraform SonarCloud and Dependabot Jira, PagerDuty and Slack Python and Bash What You'll Do Own and continuously improve cloud security posture across GCP organizations and AWS accounts, including connector coverage, runtime sensor deployment on production clusters, custom policy development, finding-triage baselines, and integrations with Jira, PagerDuty, and Slack; Operate and evolve the edge security layer, centralizing internet-facing protection through Cloudflare WAF, bot management, rate limiting, DNS/TLS, and origin routing for customer-facing production zones; Tune security rules using real production traffic, manage allow-list requests, and enable other teams to use edge-security tooling effectively; Support and automate vulnerability management and secure configuration, maintaining the intake of Wiz, SAST, penetration-test, and customer-reported findings, defining remediation baselines, and driving owners to closure; Participate in security incident response for cloud events, including DDoS and bot attacks, supply-chain alerts, credential exposure, and data-handling incidents, while creating and maintaining detection, triage, and mitigation runbooks; Help secure the software supply chain by owning SAST reporting in SonarCloud, dependency scanning with Dependabot, container base-image hardening, and the selection of SBOM and SCA tooling, and publish release-level security reports for engineering teams; Produce technical evidence for SOC 2, PCI DSS, ISO 27001, and NIS2, including evidence of log-sink configuration and retention, access reviews, authenticated scanning, and IAM remediation, and map Wiz controls to relevant frameworks to make evidence collection repeatable; Enable security self-service by training Platform, CloudOps, and Product Engineering teams on the tools they use, including Wiz and Cloudflare administration, mapping service catalogues to owners, and automating recurring customer-security and issue-triage reporting through scripting and AI-assisted workflows; Advise and partner with engineering teams on the security of new platform integrations and AI/RAG services, contributing to the annual cloud-security roadmap and target-state architecture; Job Requirements 5+ years of experience in cloud security or platform engineering with a security focus, including hands-on experience with GCP or AWS across IAM, audit logging, log routing, network security, and workload protection; Production experience with a CNAPP/CSPM platform, such as Wiz (preferably) / Prisma Cloud / Orca / Google Security Command Center, including policy authoring, integrations, and runtime protection; Hands-on administration of a WAF, CDN, and bot-management stack at scale; Strong Terraform experience, including building modules for security tooling and WAF configuration, reviewing changes, and managing configuration drift and legacy infrastructure; Experience with vulnerability management across cloud infrastructure, containers, and code, including SAST, SCA/dependency scanning, container image hardening, and penetration-test remediation tracking; Experience routing cloud security signals to a SIEM or security-monitoring platform, such as Wazuh, Microsoft Sentinel, Google Security Operations, or Datadog Security Monitoring, and integrating actionable alerts with PagerDuty and Slack; Scripting skills in Python or Bash for automation and security reporting; Security incident-response experience in a production environment, including developing runbooks and managing vendor escalations; Clear written and verbal communication skills, with the ability to train engineering teams and document security decisions; Nice To Have Experience automating security workflows, such as report generation and issue triage, with AI-assisted or LLM-based tooling; Experience working across both GCP and AWS, experience with Azure; Familiarity with Rego, OPA, or other policy-as-code languages; Experience with identity and access-management tooling, including Okta SSO/SCIM, PAM solutions, and least-privilege reviews for cloud IAM; Experience facilitating OWASP SAMM assessments, threat-modelling sessions, or security-champions programs; Airline or travel-industry experience, including PCI-scoped payment flows, partner integrations, and customer-facing security reporting; Experience supporting compliance with PCI DSS, SOC 2, ISO 27001, or NIS2; Certifications such as Google Professional Cloud Security Engineer, CCSP, or AWS Certified Security – Specialty; What Do We Offer The global benefits package includes: Technical and non-technical training for professional and personal growth; Internal conferences and meetups to learn from industry experts; Support and mentorship from an experienced employee to help you professional grow and development; Health insurance; Sports activities to promote a healthy lifestyle; Flexible work options, including remote and hybrid opportunities; Referral program for bringing in new talent; Work anniversary program and additional vacation days.
Location: Bengaluru, Karnataka, India Responsibilities: Supports UK, Ireland, Malta, Sweden, Finland, Norway, and Denmark products across the product portfolio. Supports the team with regulatory strategies (local and regional) that are in line with the business plan Supports the team with regulatory activities for National and/or European procedures (Decentralized, Mutual Recognition) as appropriate. For example, but not limited to: Prepares and compiles regulatory submissions, response to questions, renewals, post submission/approval activities (including relevant updates to external websites such as emc, medicines.ie and In-Demand) Supports ad hoc projects (e.g., compliance reviews, audit preparation etc.) Signs off on packaging material, leaflets, and SmPCs (as appropriate) Supports the compilation of the Northern Cluster team metrics for the EMEA biannual metrics report Supports all regulatory activities in Malta Ensures regulatory compliance within the department to include: The maintenance of global, regional, and local databases Adherence to processes, SOPs, work instructions, and job aids Updates to relevant local and global databases to track current product information Supports team with Calls for Information (CFI) and assist in any Pharmacovigilance- related activities within the Northern Cluster, which may include: Receiving and monitoring responses to CFIs through liaison with UK and EAME colleagues Ensuring responses are submitted in a timely manner and that they are in line with standard procedures and metrics established by the VP Regulatory Affairs in European Regulatory Provide support and responses to ad hoc requests received from UK PV group or Global Reg Med Mailbox Supports the team with regulatory activities for National and/or European procedures (Decentralized, Mutual Recognition) as appropriate. Ensures regulatory compliance within the department Experience/Qualifications: Bachelor's/Master's degree in Life Science/Pharma Minimum of 5 ~ 8 years of relevant work experience working within a Regulatory Affairs Department (e.g., pharmaceutical, cosmetic, food supplements, etc.), with direct accountability for deliverables or a combination of direct Regulatory Affairs experience of CMC, Quality, or Regulatory Operations.
Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Inference organization serves Claude to millions of users and enterprise customers, across our own products and the world’s largest cloud platforms, with the speed, reliability, and efficiency that frontier AI demands. The stack that makes this possible is deep and tightly coupled: accelerator kernels, an in-house inference engine that manages the entire token path for both production and research workloads, distributed routing, autoscaling, and capacity management. Every layer affects the others, often in ways that are hard to see in isolation. We build across GPUs, TPUs, and Trainium, and the complexity of building, testing, and shipping inference software grows with every platform we add. We're looking for a Technical Program Manager to drive the programs that scale it. The work spans four closely coupled areas: Scaling and infrastructure. Routing, autoscaling, and capacity management for the serving fleet, and bringing new capacity online. Velocity. The toolchains, development environments, and CI/CD that let inference engineers build, test, and ship across every accelerator platform. Inference engine. The software between the accelerator kernels and the routing layer that serves every request. Performance. Improving throughput, latency, cost, and reliability across the stack, with correctness treated as part of performance. This is not a status-tracking role. You'll own outcomes end to end, often where no single team is accountable for the whole picture. Much of your value comes from crossing boundaries into Research, Safeguards, Security, Compute, Infrastructure, API, and our cloud and silicon partners, and bringing back the requirements and dependencies that no team sees from inside its own space. There is little process to inherit, and we want to keep it that way: you'll build the minimum machinery the work needs and remove it when it stops helping. And because this is Anthropic, you'll have Claude as a collaborator. We expect TPMs on this team to push hard on what AI-assisted program management and fleet operations can look like. Key responsibilities Own the programs that scale Claude’s serving fleet across accelerator and cloud platforms, from early direction through delivery. Drive new capacity online end to end, working across compute, infrastructure, security, networking, and inference teams so one person is accountable for the whole path. Build visibility into supply, demand, and utilization with capacity and finance partners, and drive trade-offs among utilization, cost, latency, and reliability to a clear decision. Lead reliability programs and large migrations without disrupting production traffic or research, and make sure incident follow-ups land in team roadmaps. Drive the programs that make inference engineers faster: define the productivity metrics that matter, find the bottlenecks, and improve how software is built, tested, and released across platforms, in step with Anthropic’s central Infrastructure org. Coordinate roadmaps and priorities across the production, research, and safeguards needs that depend on the same teams. Track performance and efficiency work from opportunity to measured impact in production, with correctness held as a release criterion. Own inference readiness for model launches alongside our launch TPMs. Minimum qualifications 7+ years of experience as a TPM, or in an equivalent engineering or SRE lead role, owning large multi-team infrastructure programs end to end in production distributed systems, ML infrastructure, or cloud platforms. You can speak to the outcomes in detail, including where a program slipped and what you did about it. Technical fluency in large-scale serving infrastructure, including request routing and load balancing, autoscaling, capacity planning, cluster orchestration, deployment and rollout, and observability. You know enough to challenge a design, find the real risk, and add value beyond tracking. A working understanding of how LLM inference uses hardware (prefill and decode, batching, caching, compute versus memory bandwidth versus interconnect), or a track record of getting deep in an unfamiliar technical domain quickly. A track record of building program mechanisms from scratch on ambiguous, fast-moving efforts, and of retiring process that has stopped earning its keep. The ability to drive outcomes across organizations you don't manage, with competing priorities and unclear decision ownership. You read people and rooms well, know when to push and when to listen, and earn the trust of senior engineers and researchers. Strong written communication, including plans, reviews, and executive updates that many teams depend on. Low ego and high ownership. You do whatever the program needs, whether that is writing a script, running an incident bridge, or chasing a quota, and you care more about the outcome than about scope or credit. Care about Anthropic's mission and about serving frontier AI safely and reliably. Preferred qualifications Direct experience with LLM or ML inference serving at scale, such as model servers, batching and scheduling, KV caching, quantization, speculative decoding, or multi-model routing. Experience with accelerator infrastructure (GPU, TPU, or Trainium), including cluster bring-up, hardware qualification, or running one workload across more than one accelerator platform. Experience managing capacity across multiple clouds or regions, including demand forecasting, headroom policy, cost modeling, or unit economics for compute-heavy services. Experience with developer productivity, release engineering, or CI/CD at scale, especially for hardware-dependent workloads, and with using engineering metrics to measurably raise velocity. Experience running performance or efficiency programs, with enough grounding in rooflines, kernels, ML compilers (XLA, Triton, Neuron), numerics, or collective communication to reason about trade-offs with the engineers doing the work. Familiarity with Kubernetes-based orchestration and job scheduling. Experience working with research teams and turning their needs into infrastructure requirements. Practical experience using AI tools in your own workflow, including building automations or agents, and clear ideas about where they help and where they don't. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $290,000 — $435,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Container runtimes were designed for general-purpose software workloads. AI inference is not a general-purpose workload. Running large models at production scale exposes cracks in every layer of the container stack: runtimes unaware of GPU memory constraints, images that take minutes to pull when a model needs to scale to thousands of replicas, and isolation mechanisms that weren’t designed for the multi-tenant serving environments that production AI requires. The tools the industry has relied on for a decade weren’t built for this, and patching around those limitations at higher layers only goes so far. Baseten owns the entire pipeline, from the moment a developer pushes a model to the moment a request gets a response. That vertical ownership means we can fix these problems at the root. The Runtime Fabric team is doing exactly that: purpose-building the container runtime and storage layers for AI inference workloads, led by some of the world’s top containerd maintainers. As Engineering Manager for Storage Products on the Runtime Fabric team, you will lead the engineers who build and run the storage products behind that stack: the Baseten Delivery Network (BDN), which sits in the cold start path of every model on the platform, the snapshotters and filesystems that expose model weights and container images to a running container, and the storage that model deployment and training need next. The team is advancing the next generation of caching for inference workloads, from the origin tier to the GPU host. You will own reliability for the area as a measured outcome, report to the head of Runtime Fabric, and stay close to the code through design and code review. If you’ve managed systems engineers and have hands-on experience with caching, content-addressable storage, or distributed filesystems, we’d love to talk. EXAMPLE INITIATIVES - How the Baseten Delivery Network (BDN) makes cold starts fast https://www.baseten.co/blog/how-the-baseten-delivery-network-bdn-makes-cold-starts-fast/ - Extending BDN from model weights to container image layers, training checkpoints, and deployment artifacts - Lazy-loading snapshotters and block-level delivery (EROFS, FUSE, ublk) so a container can start before the full image or model has arrived RESPONSIBILITIES Team Leadership and Culture - Hire and grow a team of 5 to 10 systems engineers with storage, caching, and Linux expertise - Run the team’s planning and delivery: scope work against the Runtime Fabric roadmap, set priorities, and ship on a predictable cadence - Provide regular coaching, feedback, and career development support to your direct reports - Own on-call health for the team’s services, including escalation paths and follow-through on incidents Technical Direction - Guide the architecture and evolution of the Baseten Delivery Network: the tiered caching and weight delivery product that makes cold starts 2-3x faster and eliminates thundering herd failures during burst scaling events - Shape storage products tailored to Baseten’s workloads: extend BDN from model weights to container images, training checkpoints, and deployment artifacts, and define the interfaces that model deployment, training, and customers use to reach them - Oversee the on-host side of delivery: lazy-loading snapshotters, EROFS and overlayfs layouts, and block-level delivery (FUSE, ublk) for multi-gigabyte files - Own reliability of the delivery path as a measured outcome: end-to-end instrumentation from snapshotter initialization to first inference request, targets for cold start and cache behavior, tolerance for failing upstream registries and object stores, and safe rollout of changes to a path every customer depends on - Make the delivery path work across heterogeneous clusters and cloud providers, each with its own object store and network - Review designs and code across the area, and take on hands-on work where it unblocks the team - Champion the team’s contributions back to containerd and the snapshotter ecosystem alongside the maintainers on the Runtime Fabric team Cross-Functional Partnership - Act as the point of contact for storage across Baseten, ensuring model deployment, training, and platform teams have the integration support they need - Optimize requirements for the underlying storage platforms with the infrastructure team: object storage, local NVMe and block storage, and network bandwidth per cluster, so that capacity and provider decisions account for what the delivery path needs - Manage the team’s dependencies in both directions: sequence work that model deployment, training, and infrastructure teams block on, and negotiate interfaces and timelines with the teams and upstream projects the storage path depends on - Work with the head of Runtime Fabric and product stakeholders to prioritize storage investments based on customer impact and infrastructure reliability - Communicate team progress, technical trade-offs, and incidents clearly to the team and to leadership REQUIREMENTS - Experience managing a team of engineers in a systems, infrastructure, or storage context, including hiring and performance management - Hands-on background in distributed storage systems, content-addressable storage, or large-scale caching infrastructure - Strong systems programming background in Go, Rust, and/or C/C++, with the ability to engage credibly in code reviews and architectural discussions - Working knowledge of the Linux storage stack: filesystems, the page cache, block devices, and mounts - Understanding of how container images are structured, stored, and delivered at scale - Strong written and verbal communication skills, with the ability to influence without authority across teams NICE TO HAVE - Contributions to containerd/containerd, snapshotter projects (stargz, soci, nydus, overlaybd), distribution/distribution, or closely related open-source projects - Familiarity with lazy-loading snapshotters or peer-to-peer image distribution - Experience with EROFS, FUSE, ublk, or io_uring - Experience building or operating CDN, object storage, or large-scale caching infrastructure - Experience running storage services on Kubernetes BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Задачи: — Проектировать и разворачивать инфраструктуру с нуля. — Настраивать CI/CD пайплайны для фронта и бэка. — Поднимать и сопровождать кластер Docker Swarm и выстраивать процессы деплоя. — После переезда спроектировать и провести миграцию на Kubernetes. — Администрировать кластер Percona XtraDB Cluster (отказоустойчивость, бэкапы, восстановление). — Настраивать мониторинг, алертинг и логирование. — Работать в связке с командами разработки. — Участвовать в технических переговорах с подрядчиками. Требования: — Опыт коммерческой работы в DevOps или SRE от 5-ти лет. — Реальный опыт проектирования инфраструктуры с нуля, а не только поддержка существующей. — Опыт работы с Docker Swarm в продакшне. — Уверенное знание Kubernetes в продакшне. — Опыт настройки GitLab CI/CD с раннерами и пайплайнами. — Понимание сетевой модели и проксирования через Nginx. — Опыт эксплуатации Percona XtraDB Cluster/Galera в продакшне (кворум и split-brain, SST/IST, bootstrap кластера после падения, бэкапы через Percona XtraBackup). — Опыт работы с Zabbix. — Опыт с отечественными облачными провайдерами (Yandex Cloud). — Знание IaC-инструментов (Terraform, Ansible). Условия: — Удаленная работа или возможность работать как в офисе клиента, так и в офисе SkillStaff в центре Москвы на Воздвиженке. — Белая зарплата и удобный график работы. — Возможность выбора проектов для профессионального роста. — Обмен опытом и получение знаний через участие в разных проектах и совместную работу с коллегами.
Location: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. Cloud Platform Engineer An overview of this role As a Cloud Platform Engineer on the Runway team, you'll help design, build, and maintain the infrastructure and developer tooling that powers our engineering organization. You'll advance our Kubernetes-based platform, mature our GitOps practices, and expand infrastructure as code adoption across the business. This hands-on role brings together infrastructure, automation, and developer experience, helping application teams deploy and operate their services. What you’ll do Operate and improve production Kubernetes clusters across cloud environments, managing upgrades, scaling, and reliability throughout the cluster lifecycle. Own and extend Argo CD-based GitOps workflows, maintaining ApplicationSets, managing sync policies, and enforcing deployment standards across environments. Write, review, and maintain reusable Terraform modules, with clear practices for state management and drift detection. Monitor platform health, respond to incidents, conduct post-mortems, and improve availability, performance, and observability. Collaborate with application teams to onboard services, and create documentation, runbooks, and self-service tooling that improves developer productivity. Implement role-based access control, network policies, and secrets management to meet infrastructure security and compliance requirements. Integrate platform capabilities with continuous integration and continuous delivery (CI/CD) pipelines to support end-to-end delivery workflows. What you’ll bring Experience operating Kubernetes in production and working with at least one major cloud provider: Amazon Web Services, Google Cloud, or Microsoft Azure. Experience with Argo CD or comparable GitOps tooling, such as Flux. Proficiency in Terraform for cloud infrastructure provisioning, including remote state, workspaces, and module design. Ability to write scripts and automation in Python, Bash, or Go. Familiarity with Helm for Kubernetes package management. Understanding of networking fundamentals, including the Domain Name System (DNS), load balancing, ingress, and service mesh concepts. Clear written and verbal communication, with the ability to document systems and collaborate across teams. Optional: experience with managed, multi-cluster, or multi-region Kubernetes, service meshes, policy as code, observability, or Kubernetes-native infrastructure as code; open source or platform tooling contributions; or relevant certifications. About the team The Runway team builds and maintains infrastructure and developer tooling for GitLab's engineering organization. Its work centers on a Kubernetes-based platform, GitOps delivery practices, and infrastructure as code. The team collaborates with application teams to onboard services and improve developer productivity through documentation, runbooks, and self-service tooling. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $115,000 — $194,000 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .
Location: Paris ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE ROLE As a Research Engineer, GPU performance, you will sit at the heart of that spectrum: your low-level work directly determines how fast our frontier models can be trained and served. Working hand-in-hand with Research Scientists, you'll make every GPU count. Mistral AI is hiring an expert in pushing large language model's GPU utilization and performance to their limits.. In this role, you will own the performance of our models end-to-end: writing the low-level code that extracts the maximum capacity from high-end hardware, and rethinking model architectures so they run efficiently at scale. WHAT YOU WILL DO - Develop low-level code that takes full advantage of high-end GPUs and maxes out their capacity — from custom kernels to memory-layout and communication optimisations. - Rethink parts of the generative model architecture to make them more suitable for efficient inference, in collaboration with Research Scientists. - Integrate low-level efficient code into a high-level MLOps framework, so that optimisations benefit every training run and deployment rather than a single experiment. - Profile, benchmark and squeeze performance out of large-scale training and inference on thousands of GPUs. - Model LLM execution on various GPUs with high fidelity to assess hardware usage and build serving performance estimates. WHAT WE'RE LOOKING FOR - High technical competence for writing custom low-level kernels and pushing GPUs to their limits. - High expertise in the distributed computation infrastructure of current-generation GPU clusters. - Overall understanding of the field of generative AI; knowledge of, or interest in, fine-tuning and using language models for applications. - Strong software-design instincts: testing, code review, CI/CD. - Self-starter, low-ego, collaborative. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.
Location: Stockholm ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you’ll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You’ll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You’ll own durability and cost at petabyte scale, from streaming and batch replication between origins to garbage collection over billions of objects. You’ll work across the stack, from local disk and page cache to distributed blob storage and garbage collection, and you’ll help shape what storage becomes next as we push storage closer to workloads. WHAT YOU’LL WORK ON: - Build P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicate data across multiple blob storage providers - Automate garbage collection across hundreds of petabytes of data - Deploy colocated storage clusters to datacenters to accelerate high-throughput customer workloads YOU MAY BE A FIT IF: - You have 5+ years of experience writing high-quality production code - You’ve built high-performance distributed storage or caching systems at a large scale (the more challenges you’ve worked through, the better) - You have strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - You have strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - You’re willing to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVE: - Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems - Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration) - Experience with data engineering at petabyte scale - Prior experience with Rust
Location: Canada About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. Customer Experience: The Customer Experience Team at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community. The role We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps . As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines. You’re welcome to work remotely from Canada. Your responsibilities will include: Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices. Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers. Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI. Act as a single point of expertise of customer scenarios for product, technical support, marketing teams. Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.) We expect you to have: Bachelor's degree or foreign equivalent in a related field, or an equivalent combination of education and relevant experience 5+ years of customer-facing technical pre-sales experience, with pre-sales as a primary responsibility, and demonstrate ownership of technical discovery, solution architecture, customer presentations, and proof-of-concept delivery for cloud infrastructure or AI platforms, translating customer requirements into solutions and guiding technical buying decisions. 5+ years of experience utilizing Infrastructure as Code (IaC) to automate the deployment, configuration, and management of scalable cloud infrastructure and network architectures. 5+ years of Kubernetes experience designing, provisioning, and operating clusters, including node management, networking (CNI), storage (CSI), scheduling, scaling, and troubleshooting beyond managed-service abstractions. 5 years of experience developing Python-based solutions for cloud infrastructure automation, systems integration, and technical problem-solving. It will be an added bonus if you have: 3+ years of experience with GPU computing for machine learning and artificial intelligence workloads as training and inference. Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow) Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch) Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. On Target Earnings Range $235k - $300k CAD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.
Location: Remote - United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. Customer experience: Customer experience at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community. The role We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps . As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines. You’re welcome to work remotely from the United States. Your responsibilities will include: Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices. Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers. Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI. Act as a single point of expertise of customer scenarios for product, technical support, marketing teams. Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.) We expect you to have: Bachelor's degree or foreign equivalent in a related field, or an equivalent combination of education and relevant experience 5+ years of customer-facing technical pre-sales experience, with pre-sales as a primary responsibility, and demonstrate ownership of technical discovery, solution architecture, customer presentations, and proof-of-concept delivery for cloud infrastructure or AI platforms, translating customer requirements into solutions and guiding technical buying decisions. 5+ years of experience utilizing Infrastructure as Code (IaC) to automate the deployment, configuration, and management of scalable cloud infrastructure and network architectures. 5+ years of Kubernetes experience designing, provisioning, and operating clusters, including node management, networking (CNI), storage (CSI), scheduling, scaling, and troubleshooting beyond managed-service abstractions. 5 years of experience developing Python-based solutions for cloud infrastructure automation, systems integration, and technical problem-solving. It will be an added bonus if you have: 3+ years of experience with GPU computing for machine learning and artificial intelligence workloads as training and inference. Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow) Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch) Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) Key Employee Benefits: #LI-SM2 Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 401(k) Plan: Up to 4% company match with immediate vesting. Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote Work Reimbursement: Up to $85/month for mobile and internet. Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage. Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. On Target Earnings Range $250,000 — $320,000 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.
Manage the installation, configuration, and upgrading of SAP systems, including SAP HANA, ECC, and S/4HANA, ensuring adherence to best practices and compliance requirements. Monitor system performance and proactively optimize SAP applications and databases to ensure optimal resource utilization and reliability.
Location: Valencia Workplace: OnSite ROLE HIGHLIGHTS: - Software Engineer, Simulation and Modeling - Location: Valencia - Reports to: Reports to: Laboratory Lead & Test Architect - Employment type: Permanent - Workplace model: Hybrid - Employment is subject to applicable security screening (incl. SUPO, where required) WHY THIS ROLE MATTERS: As a Software Engineer, Simulation and Modeling, you’ll build the software world the satellites live in (orbits, emitters, signals, truth and scoring) so the whole team can ask “what if” and get a number back. ICEYE is building a space-based RF constellation covering 100 MHz to 30 GHz alongside its SAR fleet, and the Experimentation Lab in Valencia is where we develop, simulate and validate that capability. Customers and our own engineers ask questions we currently answer by hand-waving: what revisit a cluster gives over an area, how many emitters we detect in a crowded scene, how geolocation accuracy moves with cluster spacing or timing error, and what a next-generation architecture choice buys. The answers need a simulation framework that models the constellation and the emitters end to end, generates the signals each satellite would see, and scores what comes out against a known truth. It doesn’t exist yet. You’ll build it, and it will become a tool used by engineers, analysts and customer-facing staff. You’ll work daily with the lab, signal processing and ground segment teams, and you’ll have direct influence on how ICEYE builds and proves this capability. WHO WE ARE ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. YOUR DAY-TO-DAY RESPONSIBILITIES - Model the constellation: orbit propagation, cluster geometry, attitude and pointing, antenna beams, access and contact windows, with spacing and timing as swept variables. - Model the emitters and the theatre: emitters as state machines with real antenna patterns, scan behaviour, modes and duty cycles, placed at order-of-battle density. Start from the lab’s real captures and extend synthetically. - Generate the signals: propagation and link modelling (path loss, delay, Doppler, ionosphere in the low band) and synthetic I/Q per satellite, at a fidelity the RF hardware and the processing chain can consume. - Own the truth together with the processing team: a truth ledger of every simulated emission, position and time, kept out of reach of the system under test, plus the association and scoring that turn a run into detection rate, false-alarm rate, geolocation accuracy and latency. - Drive the hardware together with the RF team: provide the geometry and timing the channel simulator and playback hardware need, so a recorded radar can be heard by three simulated satellites with the right delays and Doppler. - Make it a platform: versioned scenarios, seeded and reproducible runs, provenance on every result, tests, CI, documentation and an interface that non-authors can use. - Answer real questions: capacity, revisit and performance studies for the payload, product and sales teams, and architecture trades for future generations. WHAT WE’RE LOOKING FOR Must haves: - Strong software engineering in Python (and ideally a compiled language): clean architecture, version control, testing, code review, packaging - Experience building a simulation or model of a physical system that others used, and validating it against measurement or real data - Numerical and scientific computing: NumPy/SciPy or equivalent, vectorisation, performance awareness - Working knowledge of at least one of orbital mechanics and access computation, RF link budgets and propagation, or signal processing - Habits that make results reproducible: seeds, configuration management, data provenance - Clear written and spoken English Nice to haves: - Constellation, mission or system-level modeling and simulation (STK, Orekit, GMAT, Basilisk or in-house) - Radar, EW or emitter modeling; scenario or order-of-battle generation - TDOA/FDOA/AoA geolocation or estimation theory - Synthetic I/Q generation, GPU acceleration, or real-time and hardware-in-the-loop interfaces - Cloud-native deployment, containers, workflow orchestration, and data stores for large runs - A simulation framework of yours that outlived your involvement in it - Eligibility for national security clearance (an advantage) What success looks like: - 6 months: a first end-to-end scenario (cluster geometry, a handful of emitters, synthetic I/Q per satellite, truth logged, a first score) is used to answer at least one real capacity or performance question. - 12 months: a reproducible, documented framework runs without you on the team; geometry drives the RF channel simulator; real captures enter scenarios alongside synthetic emitters. - 24 months: the simulation is part of the end-to-end loop with the flatsat and ground pipeline, runs in regression, and backs performance numbers we put in front of customers. APPLICATION PROCESS - Application Screening - TA call - Hiring Manager call - Onsite interview WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. OUR COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.
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