Staff/Principal Software Engineer – AI Applications

. Own the end-to-end technical strategy for a major area of the Voyager SDK application layer .

Posted 9/25/2026full-timeRemote • NetherlandsLeadWebsite

Tools & technologies

LinuxPythonPyTorchTensorflowC++

Key responsibilities & impact

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/post-processing operators and decoders
Create reusable architectures and partner with the compiler team on difficult compilation issues
Drive integration of industry-standard model frameworks into the SDK
Define reusable libraries and architecture for low-code and no-code deployment of models and datasets
Define company-wide metadata representations for model types such as bounding boxes and keypoints
Own libraries for evaluating deployed model accuracy and visually rendering inference results on Axelera AI hardware
Take accountability for pipeline latency and throughput across supported hardware platforms
Root-cause bottlenecks and build profiling tools and frameworks for diagnosing performance issues
Represent the Applications team's technical capabilities to business stakeholders, customers and industry
Mentor and develop engineers
Drive documentation standards and best practices across the team
Help shape the Applications team's technical roadmap with commercial and product stakeholders

What you’ll need

BS/MS in Computer Science, Electrical Engineering or equivalent
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
Experience with GPU computing APIs such as OpenCL and Vulkan
Strong track record applying quantization, compression and pruning
Expert-level AI application development using Python
Extensive experience with ML libraries such as PyTorch and TensorFlow
Expert-level proficiency in Python/C++
Ability to architect, build and deploy end-to-end pipelines with quantized models at scale
Experience creating reusable frameworks
Experience training models using transfer learning
Experience with MLIR and ONNXRuntime a plus
Sound technical judgement under pressure on complex, multi-dimensional problems
Strong communication and influencing skills
Experience with high-stakes conversations with senior technical and business stakeholders
Experience representing technical work externally to customers or industry
Experience mentoring and developing other engineers
Proficient Linux skills
Practical knowledge of agile development using Jira, Git and GitHub
Self-motivated and able to set technical direction with significant autonomy
Ability to thrive in a fast-paced, collaborative startup environment

Comp & perks