At a Glance
- Tasks: Optimise GPU performance for machine learning workloads using low-level C++ programming.
- Company: Disruptive tech firm leading in ML and GPU technology.
- Benefits: Health package, tech stipend, innovation days, and adventure days.
- Other info: Dynamic environment with opportunities for personal and professional growth.
- Why this job: Join a cutting-edge team shaping the future of AI and ML technologies.
- Qualifications: Proficient in C++, GPU architectures, and machine learning algorithms.
The predicted salary is between 60000 - 80000 £ per year.
We are partnering with an exciting, disruptive technology company at the forefront of machine learning (ML) and high-performance GPU computing. This innovative firm is leveraging cutting-edge GPU technology to optimize machine learning algorithms and computational models, powering the next wave of AI and data-driven applications. Their mission is to drive performance optimization in ML and AI workloads, transforming industries such as autonomous vehicles, healthcare, and immersive gaming experiences.
We are seeking a Low-Level C++ Engineer to join their team and work directly on optimizing GPU performance for machine learning (ML) workloads. As part of the ML optimization team, you will be responsible for developing and fine-tuning GPU-level solutions that accelerate machine learning training and inference. If you’re eager to work at the intersection of low-level GPU programming and machine learning, this is the role for you.
Key responsibilities include:
- Developing and optimizing low-level C++ code for GPU hardware to accelerate machine learning workloads
- Working closely with ML engineers to implement GPU-level optimizations for ML model training and inference
- Profiling and optimizing ML workloads running on GPUs, focusing on memory management, parallelization, and performance tuning
- Developing and optimizing custom GPU drivers and frameworks for ML-specific tasks
- Collaborating with data scientists and researchers to integrate new machine learning algorithms and enhance their GPU acceleration
- Staying up to date with the latest GPU architecture and machine learning advancements
Requirements:
- Proficiency in C++ with a strong focus on memory management, multi-threading, and low-level performance optimizations
- Experience with GPU architectures (e.g., NVIDIA, AMD) and programming frameworks like CUDA, OpenCL, and TensorFlow
- Understanding of machine learning algorithms, including model training and inference, and how to optimize these for GPU-based computation
- Strong knowledge of parallel computing, vectorization, and multi-core systems for high-performance computing (HPC)
- Experience with profiling tools (e.g., NVIDIA Nsight, gdb, perf) and performance tuning in a GPU environment
- Experience working with deep learning frameworks (e.g., TensorFlow, PyTorch) is a plus
- Strong problem-solving skills and a passion for AI and innovative technology
What’s on Offer:
- Comprehensive Health & Wellness Package including mental health support and fitness programs
- Tech Upgrade Stipend for personal setups (monitors, laptops, or VR headsets)
- Innovation Days to explore personal projects and experiment with new technologies
- Adventure Days: One paid day each quarter to engage in personal hobbies or exploration
- Market-leading learning and development with access to exclusive courses and conferences
- A unique opportunity to influence the future of AI and ML technologies at the cutting edge
If you are a Low-Level C++ Engineer looking to join one of the world’s most elite teams, please apply for more information.
C++ Engineer (Low Level) employer: Hunter Bond
Join a pioneering technology firm in London that is redefining the landscape of machine learning and GPU computing. With a strong emphasis on employee well-being, the company offers a comprehensive health and wellness package, innovative days for personal projects, and a tech upgrade stipend to enhance your work environment. This dynamic workplace fosters a culture of collaboration and continuous learning, providing exceptional growth opportunities for those passionate about AI and cutting-edge technology.
StudySmarter Expert Advice🤫
We think this is how you could land C++ Engineer (Low Level)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your C++ projects, especially those related to GPU programming and machine learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your low-level programming knowledge and GPU optimisations. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace C++ Engineer (Low Level)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your C++ skills and experience with GPU architectures. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about low-level programming and machine learning. We love seeing enthusiasm, so let your personality come through while keeping it professional.
Showcase Your Problem-Solving Skills:In your application, mention specific examples where you've tackled complex problems, especially in GPU performance tuning or ML workloads. We’re looking for those who can think critically and innovate!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Don’t miss out!
How to prepare for a job interview at Hunter Bond
✨Know Your C++ Inside Out
Make sure you brush up on your C++ skills, especially around memory management and multi-threading. Be ready to discuss specific projects where you've optimised low-level code, as this will show your practical experience.
✨Familiarise Yourself with GPU Architectures
Since the role focuses on GPU performance, it’s crucial to understand different architectures like NVIDIA and AMD. Prepare to talk about how you've used CUDA or OpenCL in past projects, and be ready to explain the impact of your work on performance.
✨Understand Machine Learning Fundamentals
Get a good grasp of machine learning algorithms and how they can be optimised for GPU computation. Be prepared to discuss any relevant experience you have with frameworks like TensorFlow or PyTorch, as this will demonstrate your ability to collaborate with ML engineers.
✨Showcase Your Problem-Solving Skills
During the interview, highlight your problem-solving abilities by discussing challenges you've faced in previous roles. Use specific examples that illustrate your thought process and how you approached optimisation tasks, as this will resonate well with the team.
