Role Description We’re hiring a Forward Deployed Engineer to work directly with customers as they integrate our knowledge graph into their own systems. Our customers are typically data science and bioinformatics teams in pharmaceuticals or biotechs. You’ll work closely with customer technical teams to get our data products into production. That might mean loading the graph into Neo4j, exposing it through APIs, flattening it into analytical warehouses, or helping customers use it in LLM and agent workflows. Sometimes the customer team will own most of the implementation; sometimes you’ll build large parts of it yourself. In this highly impactful role; you’ll take technical ownership from trial through to a working deployment. The role is roughly 70% customer-facing delivery work and 30% contribution to our core platform. Based in our Engineering team you’ll blend customer delivery with engineering in our core platform team; turning repeated customer problems into reusable product capabilities. Key Responsibilities - Lead customer integrations - Design integrations for AI and agent workflows - Contribute to technical scoping - Drive productisation - Contribute to the platform Qualifications - Strong experience building and deploying machine-learning-based data systems - Comfortable working with the core building blocks of these systems - Machine learning or data science background is valuable - Deep experience in either machine learning or data engineering is essential Requirements - Proven experience deploying NLP systems or LLM-powered features into production - Familiarity with recommendation and retrieval systems, retrieval-augmented generation (RAG) and vector databases - Practical experience building or debugging LLM-driven workflows - Demonstrable experience designing and running model evaluation and monitoring frameworks - Hands-on experience fine-tuning transformer-based models for domain- or task-specific use cases - Proven track record of building evaluation datasets or benchmarks from scratch - Comfortable moving between different architectural approaches for storing and accessing data - Experience building MCP servers and developing APIs with a focus on ease of LLM integration - Experience with graph databases - Neo4J preferred - Experience managing schema evolution in production - Hands-on experience building or maintaining dbt projects (or equivalent transformation tooling) - Experience working with distributed compute systems such as Spark or Beam - Experience running production orchestration systems such as Airflow, Dagster, or Prefect - Experience with cloud data warehouses (Snowflake, BigQuery, Redshift) - Ability to communicate effectively with both highly technical customer groups and internally - High personal quality standards, bringing positive energy and able to thrive with ambiguity in a scale-up environment Benefits - Competitive salaries and share options - Enhanced family leave - Significant opportunities for professional development - Genuine Flexibility: Fully remote business with colleagues across the globe - Cutting-Edge Technology: Work with the latest software tools and technologies

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.