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Principal Engineer, On-Device Inference & GPU Kernels
Opera
Source: Headcount Labs · original listing ↗
Job data: Headcount Labs, ODbL 1.0. Job descriptions belong to their employers.
Source date: 11/9/2026
About this role
Make on-device AI faster at Opera, leading GPU kernel and inference optimisation across consumer hardware to bring powerful AI experiences to millions of browser users. Location: Wrocław, Warsaw (Hybrid) We're looking for a hands-on Principal Engineer to join our AI & Browser Innovation Hub in Wrocław, focusing on high-performance, on-device AI inference and GPU optimisation. In this role, you'll work at the intersection of advanced AI research and low-level systems engineering, developing solutions that make language models faster and more efficient on consumer hardware. Working closely with Opera's AI leadership, you'll take ownership of performance-critical components, from speculative decoding and GPU kernels to quantisation and memory management. You'll have the opportunity to experiment with emerging techniques, solve complex engineering challenges, and contribute to AI capabilities used by millions of Opera users. Role & Responsibilities • Speculative decoding. Train, tune and ship draft models for the models we run block-diffusion drafters (DFlash2-like), semi-autoregressive drafters with confidence-scheduled verification (DSpark), EAGLE-style heads and multi-token prediction and keep pushing acceptance length up and drafting cost down on consumer hardware. • Kernels. Write, fuse and tune kernels for attention, quantised matmul, MoE routing, sampling and draft verification, across Metal/MLX, CUDA, Vulkan and OpenVINO. • Quantisation. Design mixed-precision schemes for weights, activations and KV cache. Match formats to the hardware, from 4-bit integer on integrated GPUs and NPUs to FP8, FP4 and microscaling formats on newer GPUs, and prove what each one costs in quality before it ships. • Prefill and decode. Push time-to-first-token and tokens per second with flash and paged attention, efficient handling of sliding-window and hybrid attention, chunked prefill and kernel-level scheduling. • Tiered memory. Build hierarchical KV and context caching that spans GPU memory, system RAM and SSD, with prefix reuse, smart eviction and prefetching that hides I/O, so long contexts and multiple models fit on machines that shouldn't be able to hold them. • Making it work everywhere. Build the test matrix, performance telemetry and regression gates that catch a slow driver, a wrong numerical result or a stalled UI before users do. • Instrumentation. Expose hooks into the runtime, such as activations and attention, so research and security work can see inside models without giving up the speed of fused kernels. Job Requirements • Deep, hands-on GPU programming in at least one of CUDA, Metal/MLX or Vulkan compute, plus evidence that you've carried that work over to a second backend. • Hands-on speculative decoding experience: you've implemented or trained drafters and understand what actually drives acceptance rate and end-to-end speed-up. • A track record of making real inference workloads measurably faster in tokens per second, latency or memory with numbers you can explain. • Strong command of quantisation and its effect on model quality, including how you measure it. • Discipline about correctness. You validate numerics against a reference and measure quality, not just spee d. Nice to Have • Contributions to llama.cpp/ggml, MLX, vLLM, SGLang, ONNX Runtime, OpenVINO or similar. • Experience with drafter-training frameworks or published work on speculative or parallel decoding. • Quantisation research or tooling: GPTQ, AWQ, k-quants, MX formats, or quantisation-aware fine-tuning. • KV cache compression, offloading or paging at the systems level. • Experience with NPUs (Intel, Qualcomm, AMD, Apple Neural Engine). What's On Offer At Opera, you'll join a collaborative, international team with a flat structure, direct communication, and opportunities for professional growth. • Advanced computing resources: Access to Apple Silicon, NVIDIA (including Blackwell-class), AMD, and Intel hardware, plus cloud GPUs for model training. • Technical ownership: Lead performance-critical development of Opera's on-device AI, working directly with AI leadership. • Global impact: Build AI solutions used by hundreds of millions of browser users across diverse hardware platforms. • Research opportunities: Contribute to open-source projects and publish technical findings where appropriate. Interested? We'd love to hear from you! Applications are reviewed on a rolling basis, so we encourage you to apply soon. Please submit your CV in English. Department Talent Acquisition Locations Wrocław , Warsaw Remote status Hybrid Discover what it's like to work at Opera → Explore our people, workplaces, and ways of working through our Digital Tour. At Opera, different perspectives drive innovation. We're committed to a fair, transparent, and inclusive environment where people are valued for their skills, ideas, and contributions. Through collaboration, curiosity, and continuous learning, we create opportunities to grow and make an impact. Languages spoken Countries represented Team members About Opera Opera is a global software company with over three decades of experience in browser innovation. Founded in 1995, we develop products and services that help hundreds of millions of people worldwide access, discover, and interact with the internet. Our portfolio includes desktop and mobile browsers, gaming-focused experiences, and AI-powered technologies that continue to shape how people navigate the web. Beyond browsing, we connect users with digital content and services while creating new opportunities across advertising, gaming, and other digital ecosystems. Headquartered in Oslo, Norway, Opera has a global presence with major hubs in Poland, China, Spain, Scotland, Singapore, and Sweden, alongside operations in other countries. As a publicly traded company, Opera is listed on the Nasdaq stock exchange under the ticker symbol "OPRA". Founded in 1995 Co-workers 501 - 1,000 Turnover $614.8 million (2025 fiscal year)