GPU Datapath Design Engineer in Kings Langley

Working in the GPU Datapath team, a unique applied research team with a remit both to research and to deliver high performing hardware, you will be a vital part of the development of innovative mathematical components. You will be able to contribute to the development of our XE series of GPUs and others. No prior knowledge of digital hardware is required. Full training will be provided on both industry tools and cutting‑edge techniques developed in-house, and you will be creating your own original ideas to push out the boundary of what can be achieved.

You will:

• Work with a team of mathematically focused engineers to design optimal arithmetic hardware components.
• Have the unique chance to contribute to cutting‑edge GPU products.
• Understand, crystallise and extract the requirements for arithmetic hardware blocks with engineers throughout Imagination.
• Design and evaluate a variety of hardware architectures for implementing math intensive blocks.
• Research new techniques for implementing a vast range of mathematical operations in silicon.
• Produce patentable work in a research and invention focused environment.
• Plan and schedule your own work, whilst educating other members of the company on datapath designs.

About you: Committed to making your customers, stakeholders and colleagues successful, you’re an excellent communicator, listener and collaborator who builds trusted partnerships by delivering what you say, when you say. You’re curious, solutions orientated and a world‑class problem solver who constantly seeks opportunities to innovate and achieve the best possible outcome to the highest imaginable standard.

You'll have:

• Programming experience, especially with SystemVerilog, VHDL, C(++), Python, Tcl or shell.
• The ability to imagine and implement improvements to a whole range of processes.
• The ability to communicate complex technical information concisely and unambiguously both verbally and in writing.
• A critical mind with the ability to think both abstractly and concretely.
• Tenacity and the ability to work and communicate with others to get things done.

You might also have:

• Knowledge of CPU, DSP, or FPU architectures and debugging/testing strategies.
• Hands‑on experience with ASIC, FPGA, and physical design tools (P&R).
• Experience with computer assisted proof via industry tools or automated theorem provers.
• Experience with scientific computing and numerical libraries.
• Knowledge of floating point arithmetic and implementation.
• Experience with optimising arithmetic hardware.
• Experience in GPU/CPU design and associated methodologies such as UVM.
• Strong communication skills, both written and spoken, in English.
• Experience writing your own rigorous mathematical proofs.