Staff/Principal Software Engineer – AI Applications

About Us Axelera AI is not your regular deep-tech company. We are creating the next-generation AI platform to support anyone who wants to help advancing humanity and improve the world around us. In just five years, we have raised a total of $450 million and have built a world-class team of 250+ employees (including 60+ PhDs with more than 40,000 citations), both remotely from 20 different countries and with offices in Belgium, France, Switzerland, Italy, the UK, headquartered at the High Tech Campus in Eindhoven, Netherlands. We have also launched our Metis™ AI Platform, which achieves a 3-5x increase in efficiency and performance, and have visibility into a strong business pipeline exceeding $100 million. Our unwavering commitment to innovation has firmly established us as a global industry pioneer. Are you up for the challenge? Position Overview The Applications team develops the customer-facing components of Axelera AI’s Voyager SDK, including low-code model deployment, end-to-end pipeline development and application integration and analytics. Customers use these tools to quickly evaluate, prototype and build complete production AI solutions accelerated by Axelera AI devices. The Applications team develops cutting-edge development tools with simple APIs that ensure the solutions deployed by our customers reach the highest levels of performance and accuracy available in the market. We are seeking an experienced, technically outstanding software engineer to take ownership of a significant area of the Applications stack. This is a Staff/Principal-level role for someone who can identify and execute on opportunities requiring strong technical judgement and difficult prioritisation, push the boundaries of what’s technically achievable, and create reusable architectures that raise the bar for the wider team. You will operate with significant autonomy, navigating ambiguity where clear playbooks don’t yet exist – whether that’s compiling high-level graphical representations of ML-based pipelines, optimizing memory usage and synchronization on heterogeneous hardware targets, or architecting low-level implementations of computer vision operators for specialised processing elements – and will help shape the technical roadmap for the Applications team in partnership with commercial and product stakeholders. Key responsibilities: Owning the end-to-end technical strategy for a major area of the Voyager SDK’s application layer – translating research papers, open-source repositories and product requirements into a coherent roadmap for model deployment, pipeline development and application integration Setting technical direction for image pre/post processing operators and decoders, creating reusable architectures that raise the bar for the rest of the team, and partnering with the compiler team to resolve the most difficult compilation issues Driving the integration of industry-standard model frameworks into the SDK, defining reusable libraries and architecture used by the team and by customers for low-code and no-code deployment of models and datasets Defining company-wide metadata representations for common model types (such as bounding boxes and keypoints), and owning the libraries used across the team to evaluate deployed model accuracy and visually render inference results on Axelera AI hardware Taking accountability for end-to-end pipeline latency and throughput across supported hardware platforms, root-causing the hardest bottlenecks, and building profiling tools and frameworks that raise the bar for how the team and customers diagnose performance issues Representing the Applications team’s technical capabilities to business stakeholders and, where relevant, to customers and the industry; mentoring and developing other engineers; and driving documentation standards and best practices across the team Qualifications: BS/MS in Computer Science, Electrical Engineering or equivalent, with a substantial track record (typically 8+ years) of hands-on experience in the semiconductor and/or AI industry Deep, hands-on expertise with edge deployment frameworks such as OpenVINO or TensorRT, with a demonstrated ability to solve problems of significant technical difficulty in this space Experience with GPU computing APIs such as OpenCL and Vulkan Strong track record applying model optimisation techniques such as quantization, compression and pruning Expert-level proficiency in AI application development using Python, with extensive experience in ML libraries such as PyTorch and TensorFlow Expert-level proficiency in Python/C++ Demonstrated ability to architect, build and deploy end-to-end pipelines with quantized models at scale, and to create reusable frameworks that others can build on Experience in training models using transfer learning to leverage pre-trained models for new tasks Experience with MLIR and ONNXRuntime a plus A track record of navigating deep ambiguity and delivering outcomes without clear playbooks, exercising