At a Glance
- Tasks: Join a dynamic team to optimise ML workloads for Apple’s cutting-edge hardware.
- Company: Apple, a leader in innovation and technology with a diverse culture.
- Benefits: Competitive salary, inclusive environment, and opportunities for personal growth.
- Other info: Collaborate with developers and contribute to open source projects.
- Why this job: Make a real impact on the future of graphics and machine learning.
- Qualifications: Experience in GPU programming and a passion for machine learning.
The predicted salary is between 60000 - 80000 £ per year.
Apple’s Metal Pro Apps Ecosystem team in GPU, Graphics and Displays org provides a suite of high-performance data parallel algorithms for developers inside and outside of Apple for iOS, macOS and Apple TV. Our responsibilities encompass the frameworks, developer tools, and device drivers for the GPU and Display on Apple’s hardware. MPSGraph provides a suite of high-performance data parallel algorithms for developers to improve the ML inference potential and performance applications on iOS, macOS and Apple TV.
GGML's Metal Pro Apps and ML Ecosystem team is now seeking a world-class, driven, and dedicated engineer to work alongside developers to integrate and optimize ML workloads for Apple’s ANE and GPU silicon into their macOS and iOS applications. Are you ready to engage with developers to advance their success using Apple’s tools and technologies related to ML?
Responsibilities
- Support adoption of GPU-accelerated training by 3rd party Apps and key middleware.
- Performing in-depth analysis of an application’s full stack to drive the best possible performance across hardware families.
- Representing Apple to these 3rd party clients and open source communities, managing the relationships, and driving the engineering work.
- Analyze developers products and report on their use of the ML API, recommending optimizations, algorithms, and techniques to improve their applications.
- Contribute platform enablement and optimisations to key open source projects.
- Host developers during in-person engineering sessions.
- You will be a key source for all aspects of ML application development, including engineering, documentation, training, and relationship management.
Minimum Qualifications
- GPU compute framework development, maintenance, and optimization.
- Proven programming and problem-solving skills.
- Good understanding of machine learning fundamentals.
- Exemplary written and oral communication skills.
Preferred Qualifications
- GPU compute programming models & optimization techniques.
- Machine learning development using one or more ML frameworks (PyTorch, TensorFlow, or JAX).
- Experience with system level programming and computer architecture.
At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. As a registered Disability Confident employer, we will work with applicants to make any reasonable accommodations. Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law. At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here - in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. Learn about accessibility in Apple’s workplace.
Pro Apps ML Ecosystem Engineer, Graphics, Games, & ML in London employer: Omaze
Apple is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration within the cutting-edge fields of graphics and machine learning. Employees benefit from comprehensive growth opportunities, access to state-of-the-art technology, and a commitment to inclusivity and accessibility, ensuring that every voice is heard and valued. Located in a vibrant tech hub, Apple provides a unique environment where passionate individuals can thrive and contribute to groundbreaking advancements in technology.
StudySmarter Expert Advice🤫
We think this is how you could land Pro Apps ML Ecosystem Engineer, Graphics, Games, & ML in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who work with Apple’s tools and technologies. Attend meetups or online webinars to connect with developers and engineers; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to GPU compute frameworks or machine learning. This is your chance to demonstrate your problem-solving abilities and programming prowess, so make it shine!
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of ML frameworks like PyTorch or TensorFlow, and be ready to discuss optimisation techniques. Practise common interview questions and think about how you can relate your experiences to the role.
✨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 and engaged with our community!
We think you need these skills to ace Pro Apps ML Ecosystem Engineer, Graphics, Games, & ML in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Pro Apps ML Ecosystem Engineer. Highlight your experience with GPU compute frameworks and machine learning, as well as any relevant projects that showcase your skills.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about working with Apple’s Metal Pro Apps Ecosystem team and how your background aligns with their mission. Be genuine and let your personality come through.
Showcase Your Communication Skills:Since exemplary written communication is key for this role, ensure your application is clear, concise, and free of errors. This is your opportunity to demonstrate your ability to communicate complex ideas effectively.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows your enthusiasm for joining our team at StudySmarter!
How to prepare for a job interview at Omaze
✨Know Your Tech Inside Out
Make sure you’re well-versed in GPU compute frameworks and machine learning fundamentals. Brush up on your knowledge of optimisation techniques and be ready to discuss how you've applied them in past projects. This will show that you’re not just familiar with the concepts, but that you can also implement them effectively.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in programming or optimisation. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help you demonstrate your analytical thinking and problem-solving abilities, which are crucial for this role.
✨Engage with the Community
Familiarise yourself with open-source projects related to ML and GPU programming. If you’ve contributed to any, be ready to discuss your role and the impact of your contributions. This shows your commitment to the developer community and your ability to collaborate effectively.
✨Communicate Clearly and Confidently
Since exemplary communication skills are a must, practice explaining complex technical concepts in simple terms. You might be asked to explain your work to non-technical stakeholders, so being able to articulate your thoughts clearly will set you apart from other candidates.
