You will own technical strategy for a major area of the application layer, turning research, open-source projects, and product requirements into roadmaps for model deployment, pipeline development, and application integration. You will design reusable architectures, optimize pipeline performance across hardware platforms, develop profiling tools, and resolve complex compilation and deployment challenges. You will also guide technical direction, mentor engineers, document best practices, and represent technical work to stakeholders and customers.
Responsibilities
- Own the end-to-end technical strategy for a major area of the Voyager SDK application layer.
- Translate research papers, open-source repositories, and product requirements into a roadmap for model deployment, pipeline development, and application integration.
- Set technical direction for image pre-processing and post-processing operators and decoders.
- Create reusable architectures and partner with the compiler team to resolve complex compilation issues.
- Integrate industry-standard model frameworks into the SDK.
- Define reusable libraries and architecture for low-code and no-code deployment of models and datasets.
- Define metadata representations for common model types, including bounding boxes and keypoints.
- Own libraries for evaluating deployed-model accuracy and rendering inference results on hardware.
- Take accountability for end-to-end pipeline latency and throughput across supported hardware platforms.
- Diagnose bottlenecks and build profiling tools and frameworks for performance analysis.
- Represent technical capabilities to business stakeholders, customers, and the industry.
- Mentor engineers and drive documentation standards and best practices.
Requirements
- BS/MS in Computer Science, Electrical Engineering, or equivalent experience.
- Typically 8+ years of hands-on experience in the semiconductor and/or AI industry.
- Expertise with edge deployment frameworks such as OpenVINO or TensorRT.
- Experience with GPU computing APIs such as OpenCL and Vulkan.
- Experience applying model optimization techniques including quantization, compression, and pruning.
- Expert AI application development skills using Python and ML libraries such as PyTorch and TensorFlow.
- Expert proficiency in Python and C++.
- Experience architecting, building, and deploying end-to-end pipelines with quantized models at scale.
- Experience creating reusable frameworks.
- Experience training models using transfer learning.
- Strong technical judgment and ability to navigate ambiguity.
- Strong communication and influencing skills with senior technical and business stakeholders.
- Experience mentoring and developing engineers.
- Proficient Linux skills.
- Practical agile development knowledge using Jira, Git, and GitHub.
Benefits
- Pension plan.
- Extensive employee insurances.
- Option to receive company shares.
You will own technical strategy for a major area of the application layer, turning research, open-source projects, and product requirements into roadmaps for model deployment, pipe...
Remote
Full_time
Permanent
#Europe including the
You will lead and scale digital design across RTL, integration, and methodology. You will translate architecture into RTL, own logical design through tape-out, coordinate with verification and physical design, enforce quality practices, support silicon bring-up, and develop engineers.
Responsibilities
- Lead and grow the silicon logical design team across RTL, integration, and methodology
- Translate system and micro-architecture specifications into RTL implementations
- Own end-to-end logical design execution from concept through tape-out
- Partner with architecture, verification, physical design, DFT, software, and product functions
- Define and enforce RTL quality, coding, reuse, and design-review practices
- Oversee block-level and top-level integration against performance, power, area, and schedule targets
- Support bring-up, debug, silicon validation, and root-cause analysis
- Contribute to technology roadmap planning and IP strategy
- Mentor and develop engineers
Requirements
- Extensive digital or logical design experience for complex SoCs with multiple tape-outs
- Ability to lead and grow silicon design teams
- Expertise in RTL and micro-architecture development using SystemVerilog or Verilog
- Experience with large-scale SoC integration including CPUs, accelerators, memory subsystems, and interconnects
- Understanding of performance, power, and area trade-offs in advanced process nodes
- Experience working with verification and physical design teams to achieve functional and timing closure
- Communication skills
Benefits
- Pension plan
- Employee insurances
- Company shares
You will lead and scale digital design across RTL, integration, and methodology. You will translate architecture into RTL, own logical design through tape-out, coordinate with veri...
Remote
Full_time
Permanent
#Europe including the
You will define the hardware architecture for AI accelerator systems across server, rack, and datacenter deployments. You will translate compute, memory, and fabric requirements into hardware specifications, define host and networking integration, establish RAS requirements, and drive architecture practices for scalable platforms.
Responsibilities
- Define hardware architecture across server boards, rack integration, and datacenter deployment
- Translate compute, memory, and interconnect requirements into hardware specifications
- Specify physical interconnect and fabric infrastructure requirements and trade-offs
- Define host, storage, networking, and power-budgeting architecture
- Ensure scale-up and scale-out designs meet performance targets
- Define RAS, redundancy, hot-swap, telemetry, management, and fault-containment requirements
- Align architectural decisions with partners and internal stakeholders
- Drive datacenter system architecture methodology and best practices
Requirements
- 5+ years of system or hardware architecture experience at server or rack scale in datacenter environments
- Knowledge of scale-up and scale-out system design, distributed workload mapping, functional partitioning, and fabric architecture
- Hands-on understanding of PCIe, CXL, Ethernet, UALink, optical, and switched-fabric interconnects
- Familiarity with RAS principles, redundancy architecture, and BMC/IPMI/Redfish interfaces
- Ability to connect workload characteristics to hardware architecture and quantify performance impacts
- Leadership and cross-functional collaboration skills
- Problem-solving skills
Benefits
- Pension plan
- Employee insurances
- Company shares
You will define the hardware architecture for AI accelerator systems across server, rack, and datacenter deployments. You will translate compute, memory, and fabric requirements in...
Remote
Full_time
Permanent
#Europe including the
You will support and moderate developer communities, create and review technical content, build relationships, organise events, advocate for user needs, track community health, and encourage open-source collaboration around the SDK and AI hardware.
Responsibilities
- Respond to technical questions and moderate community discussions
- Help developers resolve deployment issues
- Create product updates, tutorials, social content, and newsletters
- Review and fact-check AI-assisted content
- Build relationships with influencers, AI leaders, and power users
- Organise community events, webinars, and meetups
- Gather product feedback and advocate for requested features
- Maintain forum organisation and response-time service levels
- Track community engagement and health metrics
- Use AI-assisted analysis to identify trends
- Encourage SDK contributions and help resolve public technical issues
Requirements
- Understanding of the AI hardware landscape
- Community management or developer relations experience in a technical company
- Credibility within AI or developer communities
- Technical communication skills
- Experience with GitHub, forums, Discord or Slack-style tools, social channels, and community management tooling
- Fluency with AI tools for writing, research, analytics, and content generation
- Understanding of the software and SDK development lifecycle
- Maker-community experience or interest
- Community strategy
- Engagement-data analysis
Benefits
- Pension plan
- Employee insurances
- Company share option
- Flexible working arrangement
- Fully remote work from any European country including the United Kingdom
You will support and moderate developer communities, create and review technical content, build relationships, organise events, advocate for user needs, track community health, and...
Hybrid
Full_time
Permanent
#Hybrid/Remote - Europe (incl. UK), Albania (remote), Bristol (on-site) (+16 more)
You will establish and lead an infrastructure systems engineering division. You will define board- and system-level product roadmaps, review designs, lead validation and production readiness, shape platform firmware and thermal strategies, and work directly with customers and manufacturing partners.
Responsibilities
- Build, structure and mentor a multidisciplinary infrastructure systems engineering organization.
- Define the roadmap for PCIe accelerator cards, OAM modules, baseboards and rack systems.
- Lead system implementation across schematics, PCB design, high-speed signaling, memory, power and thermal integration.
- Own execution from concept through validation, qualification and mass-production readiness.
- Drive BMC management, platform firmware, secure boot, RAS and telemetry engineering.
- Lead thermal and mechanical strategies for high-power accelerator platforms.
- Align board and system execution with embedded AI engineering leadership.
- Refine platform requirements with architecture, product, silicon, SDK and software stakeholders.
- Engage customers, integrators, hyperscalers, cloud operators and OEM/ODM partners.
- Define engineering processes, documentation standards, validation methods and quality gates.
- Resolve technical risks, escalations and root-cause investigations.
- Own engineering budget, capital expenditure, external spend and vendor relationships.
Requirements
- 15+ years of hardware engineering experience for complex electronics products.
- At least 5 years of senior leadership experience running multidisciplinary teams.
- Experience shipping datacenter- or server-class compute hardware into volume production.
- Expertise in PCIe, CXL, high-speed SerDes, server memory, power delivery, VRM design, PCB layout and SI/PI.
- Experience with BMC management, Redfish, IPMI, UEFI, BIOS, secure boot and RAS.
- Knowledge of datacenter thermal and mechanical design.
- Experience working with tier-1 CMs and ODMs.
- Ability to review schematics, layouts, simulations and lab validation data.
- Fluent English.
Benefits
- Pension plan.
- Employee insurances.
- Option to receive company shares.
You will establish and lead an infrastructure systems engineering division. You will define board- and system-level product roadmaps, review designs, lead validation and production...
Remote
Full_time
Permanent
#United Kingdom
You will turn market and customer requirements into evaluation criteria, benchmark automotive workloads, and identify gaps in the software stack. You will validate safety-related integrations, contribute to collaborative R&D projects, build demonstrators, and provide technical recommendations.
Responsibilities
- Translate market and customer requirements into testable evaluation criteria.
- Verify solution capabilities and maintain requirements-versus-capability reports.
- Define and run benchmarks for automotive use cases.
- Port, quantize and optimize automotive workloads.
- Build reproducible benchmark suites and competitive comparisons.
- Maintain benchmark automation, regression tracking and dashboards.
- Prototype integration into automotive operating systems and middleware.
- Contribute to ASIL-B and ASIL-D software-stack validation.
- Assess OEM and Tier-1 integration effort and prioritize findings.
- Own technical work packages, deliverables, milestones and demonstrators in collaborative R&D programs.
- Track automotive AI and ADAS trends and recommend product and engineering priorities.
Requirements
- 4–8 years of embedded software or application engineering experience in automotive or automotive semiconductors.
- Embedded C and Python experience for tooling and test automation.
- Experience with real-time systems and safety-qualified development in an ASIL-B or ASIL-D context.
- Knowledge of ISO 26262 requirements, safety mechanisms, diagnostics and supporting evidence.
- Embedded target development, board bring-up, drivers, BSPs, cross-compilation, tracing, debugging, CI and MISRA experience.
- Experience with embedded Linux and exposure to QNX or AUTOSAR.
- Bench or HIL validation across the automotive temperature range.
- Clear technical writing.
- Fluent English.
- Ability to travel approximately 15%.
Benefits
- Pension plan.
- Employee insurances.
- Option to receive company shares.
- Structured ramp-up with direct R&D support.
You will turn market and customer requirements into evaluation criteria, benchmark automotive workloads, and identify gaps in the software stack. You will validate safety-related i...
Remote
Full_time
Permanent
#Europe (including the UK)
You will build agent capabilities, execution environments and software integrations. You will deploy and optimize models and inference workloads, validate hardware and platform behavior, investigate failures, maintain reliable operations, and create clear setup and operational documentation.
Responsibilities
- Build agent systems, intelligent tools and application integrations.
- Develop secure and scalable execution environments for AI workloads.
- Build and maintain accelerated-computing access and remote workload execution capabilities.
- Deploy and optimize computer-vision models, LLM services and inference infrastructure.
- Own implementation, hardware validation and production operation.
- Test functionality, security boundaries, hardware behavior and failure recovery.
- Write documentation, reproducible setup instructions and operational runbooks.
- Investigate failures across models, inference SDKs and execution environments.
Requirements
- Experience building with AI agents, model APIs and tools.
- Understanding of agent state management and failure recovery.
- Ability to use coding agents while retaining ownership of technical decisions.
- Experience with tool calling, structured outputs, streaming or MCP.
- Knowledge of AI workloads across applications, hosts and accelerated hardware.
- Linux, process, resource-allocation and software-stack troubleshooting experience.
- Knowledge of permissions, credentials and workload isolation.
- Experience deploying computer-vision models and LLM services.
- Ability to assess accuracy, latency, throughput and resource use.
Benefits
- Pension plan.
- Employee insurances.
- Option to receive company shares.
You will build agent capabilities, execution environments and software integrations. You will deploy and optimize models and inference workloads, validate hardware and platform beh...
Remote
Full_time
Permanent
#Europe (including the UK)
