Role Description - Help build and improve automation, tooling, and infrastructure that supports AI workloads - Support the development of operational systems and platform services - Assist in defining and maintaining basic SLOs/SLIs and monitoring dashboards - Participate in incident response, troubleshooting, and post-incident reviews - Investigate and help resolve performance and reliability issues across systems - Collaborate with Engineering, Networking, and Infrastructure teams to improve system stability - Contribute to improving availability, scalability, and operational efficiency - Learn from senior engineers and grow your expertise in reliability engineering Qualifications - 2–5 years of experience in Site Reliability Engineering, Systems Engineering, or Software Engineering in Data Center Environment - 2+ years programming skills (e.g., Python, Go, or similar) with interest in automation and tooling - Working knowledge of Linux systems, networking concepts, and distributed systems - Experience troubleshooting system or application issues in production environments - Familiarity with monitoring or observability tools (e.g., logs, metrics, dashboards) - Strong willingness to learn and improve reliability and operational practices - Ability to work in fast-paced environments and collaborate across teams Requirements - Exposure to cloud platforms, Kubernetes, or virtualized/bare-metal environments - Experience in AI, GPU workloads, or high-performance computing (HPC) - Basic understanding of high-performance networking concepts (e.g., InfiniBand, RDMA) - Exposure to production monitoring or alerting systems at small or medium scale Benefits - Collaborative, supportive, and innovative environment - Highly competitive package (base + equity) with reviews every 12 months - Dynamic progression plan tailored to your ambitions - Human-First Flexibility: autonomy to shape your day around life's moments - Competitive benefits package including medical, dental, vision, flexible paid time off, parental leave, and retirement plan participation

Role Description Nscale is seeking a Support Desk Engineer to provide first and second-line technical support to customers and internal stakeholders across our AI cloud platform. This role sits at the frontline of our customer experience, responsible for diagnosing, troubleshooting, and resolving issues across GPU infrastructure, cloud services, and related systems. You will act as a technical bridge between customers and engineering teams, ensuring timely resolution, high-quality communication, and continuous improvement of support processes. This position offers hands-on exposure to cutting-edge AI infrastructure while developing deep technical expertise in cloud and platform operations. What You'll be Doing - Handle incoming support tickets and technical inquiries via email, chat, and ticketing systems. - Provide timely, professional support in line with established processes and SLAs. - Troubleshoot issues across Nscale’s GPU cloud platform, infrastructure, and related services. - Diagnose and resolve common technical problems, escalating complex or systemic issues appropriately. - Manage tickets with accuracy and attention to detail, ensuring proper documentation and status updates. - Maintain clear records of support interactions and resolutions. - Track ticket progress and proactively communicate updates to customers. - Diagnose infrastructure, connectivity, configuration, and platform-related issues. - Perform system diagnostics and basic log analysis to support root cause identification. - Support customers with configuration, deployment, and optimization guidance. - Identify recurring patterns and escalate systemic problems to engineering teams. - Build and maintain strong knowledge of Nscale’s products, services, and common issues. - Contribute to internal knowledge bases, troubleshooting guides, and FAQs. - Support incident response efforts and collaborate during service-impacting events. - Work closely with Engineering, Infrastructure, Product, and Operations teams to resolve issues. - Relay customer feedback, feature requests, and platform improvement suggestions. - Identify opportunities to improve support workflows, tooling, and documentation. - Contribute to reducing ticket volume through improved self-service and automation. Key Performance Indicators - First response time and SLA adherence - Ticket resolution time - Customer satisfaction (CSAT) - Escalation quality and accuracy - Knowledge base contribution - Incident support effectiveness Qualifications - 2–4 years of technical support experience in a software, cloud, or infrastructure environment. - Strong troubleshooting and analytical problem-solving skills. - Excellent written and verbal communication skills, with ability to explain technical concepts clearly. - Experience working within structured support processes (ITIL or similar). - Ability to prioritize effectively in a fast-paced, high-growth environment. - Organized, disciplined, and methodical approach to issue resolution. - Strong team collaboration skills and customer-first mindset. Technical Knowledge - Familiarity with cloud platforms (AWS, GCP, Azure) or infrastructure environments. - Basic understanding of networking concepts and Linux/Unix systems. - Exposure to containerization technologies (Docker, Kubernetes) preferred. - Experience with ticketing systems (Jira, Zendesk, ServiceNow, or similar). - Understanding of APIs and REST services. - Familiarity with monitoring and observability tools (e.g., Prometheus, Grafana, ELK stack) is advantageous. Nice to Have - Experience supporting GPU infrastructure, HPC systems, or AI/ML platforms. - Knowledge of scripting languages (Python, Bash) for automation and diagnostics. - Experience in a fast-paced startup or scale-up environment. - Customer-facing experience in B2B SaaS or infrastructure platforms. Benefits - Collaborative, supportive, and innovative environment where contributions spark real impact. - Highly competitive package (base + equity) with reviews every 12 months. - Dynamic progression plan tailored to your ambitions. - Human-First Flexibility with a remote-first team. - Equal Opportunities Statement encouraging diverse applications. Salary Range $50,000 — $100,000 USD

Role Description We’re looking for a Datacenter Deployment Engineer. This role will be responsible for the execution of physical deployments, engaged in the design and layout of large scale GPU infrastructure projects. Responsibilities include: - Layout of IT equipment inside the datacenters - Taking BOMs and ensuring all hardware fits into available space, applying best practice to ensure day two maintainability. - Ensuring Datacenter environment maximums are adhered to: - Power - Cooling - Weight limits - Reviewing BOMs for interoperability - Ensuring optics/AOC/DAC are fit for purpose - Ensuring BOMs meet customer specifications - Ensuring BOMs meet Nscale project requirements - Structured cable designs - Defining and ensuring deployment standards - Cable pathing, length estimation and ordering - Working with Engineering teams for ensuring consistent deployments - Configure firewalls/routers for initial use - Work on initial switch base configurations - Onsite subject matter expert during deployments Qualifications - 5+ years of professional experience deploying, fixing and integrating IT infrastructure in data centre environments - Experience owning rack layouts or equipment placement within live or new-build data centres - Proven ability to review Bills of Materials (BOMs) and ensure hardware fits within space, power, cooling, and weight constraints while maintaining day-two operability - An understanding of data centre environmental limits, including power density, cooling capacity, and structural loading - Some experience validating hardware interoperability, including optics, AOC/DAC selection, and compatibility with switching platforms - Ability to ensure deployments meet customer specifications and internal project requirements - Practical experience designing, reviewing, and deploying structured cabling, including cable pathing, length estimation, and ordering - Strong ownership of deployment standards, ensuring consistent, repeatable installations across sites - Experience working closely with engineering and operations teams to deliver aligned, high-quality deployments - Hands-on experience with initial network device configuration, including firewalls, routers, and base switch configurations - Comfortable acting as the on-site subject matter expert during data centre deployments, troubleshooting issues in real time - Strong attention to detail, documentation, and operational discipline Requirements - Experience deploying GPU, HPC, or high-density compute environments - Familiarity with AI-focused or high-performance data centre architectures Benefits - Collaborative, supportive, and innovative environment - Highly competitive package (base + equity) with reviews every 12 months - Dynamic progression plan tailored to your ambitions - Human-First Flexibility with a remote-first team Equal Opportunities Statement We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds. If there’s anything we can do to accommodate your specific situation, please let us know.

Role Description We are looking for highly motivated Software Engineering Interns who are passionate about Open Source, Go programming, and Cloud Native technologies. This internship is designed as a pathway to a full-time engineering role for candidates who demonstrate strong technical ability, ownership, and the mindset to thrive in a fast-moving environment. You will have the opportunity to work on production-grade infrastructure and contribute to technologies used by enterprises worldwide. Depending on your skills and interests, you may work on CNCF ecosystem projects such as Prometheus, CloudNativePG (CNPG), Kubernetes, and others, while collaborating with experienced engineers and interacting directly with customers. What you will do - Build and contribute to cloud native software using Go. - Work on real-world engineering challenges across Prometheus, Kubernetes, CloudNativePG (Postgres Operator), and the CNCF ecosystem. - Contribute to open source projects and upstream communities where applicable. - Debug, troubleshoot, and improve distributed systems. - Collaborate with customers to understand problems and deliver practical solutions. - Take end-to-end ownership of assigned tasks, from design to implementation and documentation. - Continuously learn and adapt to new technologies and engineering practices. Qualifications - Strong interest in Open Source software and Cloud Native technologies. - Good programming skills in Go (or a willingness to become highly proficient in Go). - Solid understanding of computer science fundamentals, Linux, networking, and distributed systems concepts. - Self-disciplined, proactive, and capable of taking ownership without constant supervision. - Strong problem-solving and debugging skills. - Excellent written and verbal communication skills. - Empathy and professionalism when working with customers and teammates. - Curiosity, initiative, and a strong desire to learn by building. Requirements - Previous contributions to Open Source projects (GitHub profile, pull requests, issues, or maintainership). - Active participation in CNCF or other open source communities. - Experience with Kubernetes, Prometheus, CloudNativePG, or related cloud native technologies. - Personal projects demonstrating systems programming, distributed systems, or infrastructure engineering. - Participation in programs such as GSoC, LFX Mentorship, or similar initiatives. Internship to Full-Time This internship is intended to identify future full-time engineers. High-performing interns will be offered the opportunity to join the team as full-time Software Engineers based on their performance, ownership, technical skills, and cultural fit. Selection Philosophy We value demonstrated ability over credentials. A strong GitHub profile, meaningful open source contributions, technical depth, ownership, and the ability to communicate effectively will stand out far more than a resume alone.