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Software Engineer C

Job in Oxford, Oxfordshire, OX1, England, UK
Listing for: Recruit 12
Full Time position
Listed on 2026-01-23
Job specializations:
  • Engineering
    AI Engineer, Software Engineer
Job Description & How to Apply Below

Software Engineer C++ GPU Acceleration

Overview

We are seeking a skilled C++ Engineer with strong GPU acceleration expertise to work on cutting-edge, high-performance systems used across entertainment, engineering, and scientific applications. This role focuses on maximising GPU-based processing performance, including real-time data handling, image processing, and machine learning workloads.

You will join a collaborative software engineering team and work closely with machine learning and research specialists in an environment that values technical excellence, innovation, and a healthy work life balance.

Key Responsibilities

  • Design and implement high-performance algorithms using CUDA
  • Manage host device interactions, including memory management, data transfer optimisation, and multi-GPU support
  • Deploy and optimise machine learning models using Tensor

    RT within C++ applications
  • Profile and optimise GPU workloads using NVIDIA Nsight Systems and Nsight Compute
  • Configure GPU hardware and software stacks to maximise runtime performance
  • Evaluate and recommend appropriate GPU hardware for specific workloads
  • Clearly communicate GPU-related opportunities and constraints to non-technical stakeholders

Required Skills, Knowledge & Experience

  • Strong modern C++ development skills
  • Proven experience with CUDA and CUDA libraries
  • Solid understanding of software optimisation and performance tuning
  • Experience developing and profiling GPU-accelerated applications
  • Confidence working in performance-critical, real-time systems

Desirable (Not Essential)

  • Knowledge of networking, streaming, or video compression
  • Experience with real-time data pipelines or image processing systems

Working Environment

  • Collaborative, cross-disciplinary engineering culture
  • Close interaction with machine learning and research teams
  • Informal and supportive workplace with an emphasis on sustainable workloads
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