At a Glance
- Tasks: Optimise ML inference for edge devices and ensure reliable operation in vehicular environments.
- Company: Icehouseventures, a dynamic company fostering innovation and inclusion.
- Benefits: Hybrid work policy, competitive salary, and opportunities for professional growth.
- Other info: Enjoy a collaborative environment with exciting projects and career advancement.
- Why this job: Join us to work on cutting-edge ML technology and make a real impact.
- Qualifications: Experience in ML performance engineering and a passion for innovative tech.
The predicted salary is between 60000 - 80000 £ per year.
Icehouseventures is looking for a Staff ML Performance Engineer to optimize ML inference for edge accelerators and GPUs. You will focus on running large transformer-based models efficiently on low-cost, low-power devices, directing technical projects and ensuring reliable operation in vehicular compute environments.
This full-time role operates under a hybrid policy, balancing office collaboration with remote work. Candidates can expect a dynamic environment, fostering innovation and inclusion.
Staff ML Performance Engineer — Edge Inference Optimizer in London employer: Icehouseventures
Icehouseventures is an exceptional employer that champions innovation and inclusivity, making it an ideal place for a Staff ML Performance Engineer. With a hybrid work policy, employees enjoy the flexibility of remote work while collaborating in a dynamic office environment, fostering both personal and professional growth. The company prioritises employee development and offers unique opportunities to work on cutting-edge technology in the exciting field of edge inference optimization.
StudySmarter Expert Advice🤫
We think this is how you could land Staff ML Performance Engineer — Edge Inference Optimizer in London
✨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 projects, especially those related to ML inference and edge devices. 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 knowledge of transformer models and edge computing. 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! We love seeing candidates who are proactive and engaged. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Staff ML Performance Engineer — Edge Inference Optimizer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with ML inference and edge devices. We want to see how your skills align with optimising large transformer-based models, so don’t hold back on the details!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for ML performance engineering and how you can contribute to our dynamic environment. Let us know why you’re excited about working with edge accelerators and GPUs.
Showcase Relevant Projects:If you've worked on any projects related to vehicular compute environments or low-power devices, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions of your work!
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Icehouseventures
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest ML inference techniques, especially for edge devices. Brush up on transformer models and be ready to discuss how you would optimise them for low-cost, low-power environments.
✨Showcase Your Project Experience
Prepare to talk about specific projects where you've directed technical efforts. Highlight your role in ensuring reliable operation in challenging environments, like vehicular compute settings, to demonstrate your hands-on experience.
✨Emphasise Collaboration Skills
Since this role involves a hybrid work model, be ready to discuss how you’ve successfully collaborated with teams both in-person and remotely. Share examples of how you fostered innovation and inclusion in past projects.
✨Ask Insightful Questions
Prepare thoughtful questions about Icehouseventures’ approach to ML performance engineering. This shows your genuine interest in the role and helps you gauge if the company’s dynamic environment aligns with your career goals.
