Location & work modality EMEA / Remote Start Aug 2026 Type of Contract Contractor or FTE About Radian Arc. Radian Arc provides an infrastructure-as-a-service (IaaS) platform for running cloud gaming artificial intelligence and machine learning applications inside telecommunication carrier networks. Our teams across the USA Australia Central Europe Malaysia Singapore and Japan offer telecom operators a GPU-based edge computing platform without the need for capital expenditure facilitating low latency and improved economics for value-added services and the monetization of 5G investments. What impact you will have Design and develop the platform control plane responsible for managing GPU cloud infrastructure and distributed AI workloads. This role focuses on building the core orchestration services that provision manage and coordinate compute networking and storage resources across global GPU clusters. The Senior Software Engineer will design and implement distributed systems that power the platform's control plane enabling reliable orchestration of Kubernetes clusters GPU workloads and multi-tenant infrastructure. You will build APIs services and Kubernetes-native operators that automate infrastructure lifecycle management and provide the primitives required to run large-scale AI workloads across multiple regions. This role works closely with platform networking storage and infrastructure teams to ensure the control plane integrates seamlessly with the underlying GPU infrastructure networking fabrics and disaggregated storage systems. The emphasis is on independently delivering major control-plane components solving difficult distributed-systems and orchestration problems and improving platform reliability and operability within the broader platform direction. What you'll do Platform Control Plane Development Design and develop the platform control plane services responsible for managing GPU cloud infrastructure. Implement APIs and services that orchestrate compute networking and storage resources. Build distributed services responsible for cluster lifecycle management and infrastructure orchestration. Implement reliable state management systems for distributed infrastructure components. Kubernetes Platform Integration Develop Kubernetes operators and controllers that automate platform infrastructure. Implement cluster lifecycle APIs responsible for Cluster provisioning Cluster upgrades Node lifecycle management. Infrastructure automation. Integrate platform services with Kubernetes control planes running on bare-metal infrastructure. AI Infrastructure Orchestration Develop orchestration frameworks that manage GPU workloads across distributed clusters. Implement platform services that optimize resource scheduling and utilization for AI workloads. Integrate the platform control plane with components such as NVIDIA GPU Operator KServe Argo Workflows SLURM integration KubeVirt virtualization. Distributed Systems Engineering Build distributed systems that coordinate workloads across multi-region GPU clusters. Implement services capable of handling high-throughput infrastructure orchestration workloads. Design scalable mechanisms for distributed state management and coordination. Contribute practical design input for platform components. Reliability & Operations Engineer systems for high availability and fault tolerance. Implement observability monitoring and alerting for platform services. Participate in incident response and on-call rotations for platform systems. Perform root cause analysis and implement systemic improvements to platform reliability. Engineering Excellence Drive technical design decisions for platform components. Maintain high standards for testing CI/CD and operational safety. Participate in architecture discussions code reviews and system design. Contribute to repeatable patterns implementation quality and operational maturity within the platform software domain. Technical Stack Platform Development Go. Kubernetes controllers / operators. Distributed systems architecture. REST / gRPC APIs. Platform Infrastructure Kubernetes. Helm. GitOps workflows. AI Platform Components NVIDIA GPU Operator. KServe Argo Workflows. SLURM integration KubeVirt. Storage Integration Weka distributed storage VAST disaggregated storage StorPool HCI CSI drivers Observability Prometheus Grafana OpenTelemetry What you'll need Core Experience 5+ years of experience building distributed systems or infrastructure platforms. Strong programming experience in Go. Experience developing Kubernetes operators and controllers. Kubernetes Platform Engineering Strong understanding of Kubernetes internals and control plane architecture. Experience building infrastructure automation around Kubernetes. Familiarity with multi-tenant Kubernetes environments. Distributed Systems Experience designing and operating distributed systems at scale. Understanding of distributed state management and service coordination. Experience building reliable highly available infrastructure services. Infrastructure & Systems Knowledge Strong Linux systems knowledge. Experience troubleshooting complex production systems. Understanding of networking and storage infrastructure used by distributed systems. Operational Excellence Experience operating high-availability production systems. Familiarity with observability tooling such as Prometheus and Grafana. Experience participating in on-call rotations and incident response. Personal Attributes Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Passion for building reliable infrastructure systems at scale. What we offer Attractive compensation package reflecting your expertise and experience. A great work environment characterised by friendliness international diversity flexibility and a hybrid-friendly approach. You'll be part of a fast-growing scale-up with a mission to make a positive impact offering an exciting career evolution. Our job titles may span more than one job level. The actual base pay is dependent on a number of factors such as transferable skills work experience business needs and market demands. Our inclusive responsibility Radian Arc is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race color religion gender gender identity or expression sexual orientation national origin genetics disability age veteran status or any other protected category under applicable law.

About Radian Arc. Radian Arc provides an infrastructure-as-a-service (IaaS) platform for running cloud gaming artificial intelligence and machine learning applications inside telecommunication carrier networks. Our teams across the USA Australia Central Europe Malaysia Singapore and Japan offer telecom operators a GPU-based edge computing platform without the need for capital expenditure facilitating low latency and improved economics for value-added services and the monetization of 5G investments. What impact you will have Mission Install validate operate and maintain regional and core GPU cloud deployments across datacenter environments. This role owns the practical deployment and operational readiness of the platform stack in the field. It bridges infrastructure engineering datacenter operations networking host systems storage and platform operations. The engineer is responsible for taking a validated architecture and BOM and turning it into a working production environment including physical deployment coordination rack and cabling validation switch and host bring-up firmware and BIOS validation operating-system installation GPU and DPU validation storage integration platform stack installation acceptance testing and operational handover. The role is intentionally hands-on and cross-domain. It is not a pure datacenter technician role and it is not a pure platform engineering role. It is the person who can work in a datacenter understand cabling and optics debug host and network issues validate GPU servers support platform installation and coordinate with engineering when problems arise. The role is especially important as the platform evolves from regional deployments toward HGX-based GPU systems east-west fabrics and core AI infrastructure. This profile is focused on actual installation commissioning maintenance and operational readiness. What you'll do ### Datacenter deployment and commissioning Coordinate physical deployment activities with datacenter providers integrators logistics teams and internal engineering. Validate rack layouts elevations power feeds airflow assumptions cable paths and labeling before installation. Support rack-and-stack activities for GPU nodes CPU nodes storage nodes switches firewalls routers serial/OOB equipment PDUs and supporting infrastructure. Validate fibre and copper cabling against the deployment design including OOB north-south east-west storage and management networks. Validate optics transceivers link speeds breakout cables port mappings and redundancy assumptions. Maintain accurate as-built documentation including rack elevations cable maps port maps serial numbers asset records IP allocations and change records. ### Host and hardware bring-up Bring up GPU servers platform servers storage nodes and supporting infrastructure. Validate BIOS BMC firmware NIC DPU GPU NVMe RAID/HBA and platform firmware versions. Configure and validate BMC access using Redfish/IPMI and OOB management networks. Validate GPU visibility PCIe topology NUMA layout thermals power behavior and hardware health. Run hardware acceptance tests burn-in tests GPU stress tests network tests and storage validation before handover. Troubleshoot hardware issues across servers GPUs DPUs NICs optics cables disks memory firmware and BIOS. ### Network deployment support Support deployment and validation of OOB north-south storage and east-west networking. Work with networking engineering to apply and validate switch configurations. Validate BGP ECMP VLAN/VRF segmentation EVPN/VXLAN where applicable OVS/OVN integration and routing reachability. Validate VyOS routers OOB firewalls transit routers Citrix NetScaler/WAF and customer connectivity. Support RoCE/RDMA fabric validation for distributed AI workloads where applicable. Troubleshoot practical network issues such as link flaps optics issues incorrect polarity MTU mismatches route leaks VLAN errors packet loss PFC/ECN issues and fabric congestion. Support integration with NVIDIA Cumulus / Spectrum-X environments and assist with Cisco or SONiC-based alternatives if those become part of the roadmap. ### Platform stack installation and validation Support installation and validation of the platform stack across regional and core deployments. Install and validate host operating systems kernel versions NVIDIA drivers Mellanox/NVIDIA OFED or inbox drivers CUDA compatibility Docker/containerd KVM/QEMU and platform agents. Support CloudStack-based deployments and Kubernetes/KubeVirt-based deployments. Validate GPU passthrough SR-IOV BlueField NIC/DPU behavior VM networking and container networking. Support Kubernetes node registration GPU Operator validation CSI validation CNI validation and node lifecycle workflows. Support storage integration with StorPool Weka local NVMe or other supported storage platforms. Execute acceptance tests and produce deployment readiness reports. ### Operational maintenance and Day-2 support Perform controlled maintenance activities such as firmware upgrades switch upgrades host OS updates GPU driver updates BIOS changes and hardware replacements. Support incident response for infrastructure issues affecting GPU nodes hosts networking storage or platform components. Perform root-cause analysis for deployment and operational failures. Maintain runbooks for installation validation upgrade rollback troubleshooting and handover. Work with engineering to turn repeated operational issues into automation better validation or platform improvements. Participate in on-call or escalation rotations for regional and core environments where appropriate. ### Platform observability and validation Ensure telemetry is correctly configured for hosts GPUs DPUs switches storage OOB devices and platform components. Validate Zabbix Prometheus Grafana Loki DCGM/NVML NVIDIA NetQ or equivalent telemetry sources. Confirm that deployment health checks hardware alerts performance dashboards and operational alarms work before production handover. Support performance baseline testing for GPU network storage and host layers. Assist with NCP-related validation and benchmarking. ### Cross-team coordination Work closely with the Senior Director of Infrastructure Operations. Work closely with Staff Network Staff Storage Sr Hardware/Infrastructure Sr Platform Sr Fleet Automation Observability Product Engineering Sales Engineering and Service Delivery roles. Provide field feedback into reference architectures BOMs rack layouts cabling standards deployment playbooks and validation procedures. Coordinate with external vendors including datacenter providers systems integrators server vendors storage vendors NVIDIA and networking vendors. Act as the practical field escalation point when architecture BOM datacenter conditions and platform implementation do not align. Technical Stack - ### Hardware and datacenter GPU servers L40S RTX 6000 Pro H200 B200/B300-class systems HGX systems and future NVL72-style rack-scale systems. CPU/platform servers. Storage nodes and JBODs. PDUs BMCs serial/OOB firewalls routers switches. Rack layouts power feeds airflow cold/hot aisle containment cabling optics. DTC/DLC cooling. ### Host and systems Ubuntu Linux. Linux networking. BIOS/BMC/firmware lifecycle. Redfish IPMI. NVIDIA drivers CUDA DCGM/NVML. Mellanox/NVIDIA NICs BlueField DPUs. KVM/QEMU VFIO PCI passthrough. Docker/containerd. ### Networking NVIDIA Spectrum/Cumulus. VyOS. OVS/OVN. BGP ECMP VLAN VRF EVPN/VXLAN. RoCE/RDMA. SR-IOV. Citrix NetScaler / WAF. OOB and break-glass access. ### Platform CloudStack. Kubernetes. KubeVirt. NVIDIA GPU Operator. CSI/CNI integrations. StorPool Weka local NVMe. Terraform Ansible Bash Python. ### Observability Zabbix. Prometheus. Grafana. Loki. DCGM Exporter. NVIDIA NetQ or equivalent. Logs metrics hardware health and deployment validation dashboards. What you'll need Strong hands-on experience deploying and maintaining datacenter infrastructure. Experience with GPU HPC AI cloud private cloud or high-density compute environments including both air-cooled and liquid-cooled deployments. Experience with DTC / DLC cooling concepts including rack manifolds CDU integration facility water-loop requirements coolant specifications flow/pressure/temperature validation leak detection and cooling redundancy. Familiarity with NVL72-style rack-scale architectures including liquid-cooled GPU trays NVLink/NVSwitch domains in-rack networking high-density power delivery and OEM/NVIDIA validation requirements. Comfortable working across physical infrastructure Linux hosts networking storage and platform software. Experience bringing up servers from bare metal through production readiness. Experience with rack layouts cabling optics transceivers power OOB management and datacenter handover. Strong Linux troubleshooting skills. Practical networking knowledge across VLANs VRFs BGP ECMP OVS/OVN and routing. Experience with GPU servers NVIDIA drivers firmware PCIe topology and hardware validation. Experience with infrastructure automation using Bash Python Ansible Terraform or similar tooling. Strong documentation discipline and ability to produce accurate as-built records and runbooks. Ability to validate practical datacenter readiness for current and next-generation AI infrastructure including power density cooling model rack depth/width floor loading containment serviceability and maintenance access. Personal qualities Very hands-on and practical. Comfortable working in datacenters and remotely with smart-hands teams. Strong troubleshooting mindset across hardware network host and platform layers. High attention to detail around cabling labeling asset records and validation. Calm under pressure during deployment windows and customer-impacting incidents. Able to distinguish between a temporary field workaround and a permanent engineering fix. Good communicator who can explain field issues clearly to engineering and leadership. What we offer Attractive compensation package reflecting your expertise and experience. A great work environment characterised by friendliness international diversity flexibility and a hybrid-friendly approach. You'll be part of a fast-growing scale-up with a mission to make a positive impact offering an exciting career evolution. Our job titles may span more than one job level. The actual base pay is dependent on a number of factors such as transferable skills work experience business needs and market demands. Our inclusive responsibility Radian Arc is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race color religion gender gender identity or expression sexual orientation national origin genetics disability age veteran status or any other protected category under applicable law.

AI Engineer - FDE (Forward Deployed Engineer) (ALL LEVELS) Location Spain - Remote Req ID CSQ327R197 Recruiter Dina Hussain Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering product and developer relations as well as support internal subject matter expert (SME) teams. We view our team as an ensemble we look for individuals with strong unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers teammates and fueling your curiosity for the latest trends in GenAI LLMOps and ML more broadly. We welcome remote applicants located near our offices. Preferred locations (in priority order) London (UK) Madrid (Spain) Paris (France) and Amsterdam (NL). Reporting to Senior Manager - AI FDE EMEA The impact you will have Develop cutting-edge GenAI solutions incorporating the latest techniques from Databricks AI research to solve customer problems Own production rollouts of consumer and internally facing GenAI applications Serve as a trusted technical advisor to customers across a variety of domains Present at conferences such as Data + AI Summit recognized as a thought leader internally and externally Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for Experience building GenAI applications including RAG multi-agent systems Text2SQL fine-tuning etc. with tools such as HuggingFace LangChain and DSPy Expertise in deploying production-grade GenAI applications including evaluation and optimizations Extensive years of hands-on industry data science experience leveraging common machine learning and data science tools i.e. pandas scikit-learn PyTorch etc. Experience building production-grade machine learning deployments on AWS Azure or GCP Graduate degree in a quantitative discipline (Computer Science Engineering Statistics Operations Research etc.) or equivalent practical experience Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike Passion for collaboration life-long learning and driving business value through AI [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark to process large-scale distributed datasets Willing to travel once every 4-8 weeks to see customers (as needed) About Databricks Databricks is the data and AI company. More than 10000 organizations worldwide — including Comcast Condé Nast Grammarly and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data analytics and AI. Databricks is headquartered in San Francisco with offices around the globe and was founded by the original creators of Lakehouse Apache Spark Delta Lake and MLflow. To learn more follow Databricks on Twitter LinkedIn and Facebook. Benefits At Databricks we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age color disability ethnicity family or marital status gender identity or expression language national origin physical and mental ability political affiliation race religion sexual orientation socio-economic status veteran status and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties it is within Employer's discretion whether to apply for a U.S. government license for such positions and Employer may decline to proceed with an applicant on this basis alone.

Spanish Transcriber (Spain) Location 100% Remote global Status Project-Based (Contract) Benefits Flexible schedule work from home Compensation USD 3.00 per audio minute transcribed Please note To ensure eligibility for this project applicants must be international freelancers. Unfortunately we are unable to hire U.S. citizens Green Card holders or candidates currently residing in the U.S. POSITION SUMMARY This transcription project supports the development of talk-to-text technology. Your task involves listening to audio files from our online database and transcribing exactly what you hear including some segment labeling. You will receive detailed guidelines to follow upon joining. Compensation & Schedule Workload depends on project needs and tasks vary in length. You will be paid per audio minute. Platform Requirements Please note This project is coordinated via Upwork and all transcribers must have an Upwork profile to receive payment. Candidates who do not already have one are welcome to apply but will be required to create a profile upon being hired. RESPONSIBILITIES Accurately transcribe a variety of files in accordance with client-specific Written Domain conventions (WDCs) Maintain a thorough understanding of each client’s guidelines updating your knowledge as changes occur Produce high-quality timely work for all assigned transcription projects Reference and apply current training materials and documentation as needed Identify and report technical issues or transcription concerns to the Division Services Manager Contribute ideas for improving workflows and transcription processes Participate in additional tasks or special projects as assigned SKILLS Strong written and verbal communication skills with a collaborative team-oriented mindset Ability to manage multiple projects and deadlines in a fast-paced remote environment Exceptional attention to detail and accuracy under tight time constraints Excellent internet research skills including creative problem-solving techniques Professionalism in navigating feedback ambiguity and evolving client needs Proficient in both Mac and PC environments skilled in Microsoft Office and Google Workspace Adaptability and openness to continuous learning and feedback REQUIREMENTS Native-level (C2) proficiency in Spanish (Spain) - (eses) including the ability to read and write. If you do not possess these characteristics but wish to be considered for other roles please submit your inquiry via our Jobseekers Inquiry form. Excellent grammar/ orthography and punctuation. You will be required to take an assessment. Have an Upwork profile or be willing to create an Upwork profile High-speed internet access This project requires participants to have their own computer Access to e-mail Please note that the pay rate is in US dollars and payment will be made in US dollars. The amount in local currency will vary according to exchange rates. About Us As a global data company Productive Playhouse “PPH” is pioneering our approach to language and data services while incorporating their roots as a production company. Originally creating content to support children's language acquisition our commitment to excellence forward-thinking strategies and worldwide cultural experience has proven key for delivering exceptional service. Originally founded as an educational production company Productive Playhouse made a mark with our award-winning children’s series which taught fundamental subjects through engaging and effective programming. This early success paved the way for our evolution into a comprehensive data services provider. Since 2011 Productive Playhouse has expanded rapidly to offer an extensive suite of data services. Our current offerings include transcription translation linguistic analysis rating systems testing localization field and studio recording language skill verification and specialized data handling with a focus on sensitivity and diversity. Our commitment to innovation means we continually enhance our service portfolio to meet the evolving needs of our clients. At Productive Playhouse we are proud of our reputation for addressing complex challenges with agility and delivering premium secure data solutions across diverse environments. Our dynamic team is dedicated to maintaining the highest standards and ensuring exceptional service every time. Disclaimer The job description provided is designed to convey information essential to understanding the scope of the position and the general nature of the work performed. It is not intended to be an exhaustive list of duties responsibilities or qualifications associated with the job. Productive Playhouse reserves the right to modify or revise the job description as necessary Productive Playhouse is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive work environment for all employees. Employment with Productive Playhouse is at-will meaning that either the employee or the employer can terminate the employment relationship at any time with or without cause or notice. All offers of employment at Productive Playhouse are contingent upon the candidate’s ability to provide valid documentation of identity and eligibility to work in the United States or relevant hiring location. Productive Playhouse participates in E-Verify. Productive Playhouse provides reasonable accommodation for qualified individuals with disabilities. If you need assistance or accommodation due to a disability please contact the Human Resources Department. oTFI6OULa1

AI Engineer - FDE (Forward Deployed Engineer) (ALL LEVELS) Location France - Remote Req ID CSQ327R197 Recruiter Dina Hussain Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering product and developer relations as well as support internal subject matter expert (SME) teams. We view our team as an ensemble we look for individuals with strong unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers teammates and fueling your curiosity for the latest trends in GenAI LLMOps and ML more broadly. We welcome remote applicants located near our offices. Preferred locations (in priority order) London (UK) Madrid (Spain) Paris (France) and Amsterdam (NL). Reporting to Senior Manager - AI FDE EMEA The impact you will have Develop cutting-edge GenAI solutions incorporating the latest techniques from Databricks AI research to solve customer problems Own production rollouts of consumer and internally facing GenAI applications Serve as a trusted technical advisor to customers across a variety of domains Present at conferences such as Data + AI Summit recognized as a thought leader internally and externally Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for Experience building GenAI applications including RAG multi-agent systems Text2SQL fine-tuning etc. with tools such as HuggingFace LangChain and DSPy Expertise in deploying production-grade GenAI applications including evaluation and optimizations Extensive years of hands-on industry data science experience leveraging common machine learning and data science tools i.e. pandas scikit-learn PyTorch etc. Experience building production-grade machine learning deployments on AWS Azure or GCP Graduate degree in a quantitative discipline (Computer Science Engineering Statistics Operations Research etc.) or equivalent practical experience Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike Passion for collaboration life-long learning and driving business value through AI [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark to process large-scale distributed datasets Willing to travel once every 4-8 weeks to see customers (as needed) About Databricks Databricks is the data and AI company. More than 10000 organizations worldwide — including Comcast Condé Nast Grammarly and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data analytics and AI. Databricks is headquartered in San Francisco with offices around the globe and was founded by the original creators of Lakehouse Apache Spark Delta Lake and MLflow. To learn more follow Databricks on Twitter LinkedIn and Facebook. Benefits At Databricks we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age color disability ethnicity family or marital status gender identity or expression language national origin physical and mental ability political affiliation race religion sexual orientation socio-economic status veteran status and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties it is within Employer's discretion whether to apply for a U.S. government license for such positions and Employer may decline to proceed with an applicant on this basis alone.