At a Glance
- Tasks: Join a creative team to build and integrate ML models for Apple’s developer tools.
- Company: Apple, a leader in innovation and diversity, values your unique ideas.
- Benefits: Competitive salary, inclusive culture, and opportunities for personal growth.
- Other info: Dynamic environment with a commitment to accessibility and career development.
- Why this job: Make a real impact with cutting-edge technology and collaborate with passionate experts.
- Qualifications: Strong programming skills and experience with LLM evaluations are essential.
The predicted salary is between 60000 - 80000 £ per year.
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives.
Our Developer Publications Intelligence team seeks a creative engineer who has a robust knowledge of large language models (LLMs), Machine Learning infrastructure, and experience with LLM‑evaluations at scale. Strong engineering fundamentals are required.
As an Applied Machine Learning Engineer in the Developer Publications Intelligence team, you will join a multi‑discipline team of passionate Machine Learning and Software engineers to build and integrate ML models into existing and future tools produced by Apple for third‑party developers. We strive for excellence and believe strongly in the quality of our output. As a member of the team, you will work alongside a team of domain experts in specific core subject areas, enable cross functional collaboration with other departments at Apple, contribute to architecture discussions, code review and proposals.
Responsibilities:- Driving MLOps/LLMOps excellence within the team: including evaluation pipelines, monitoring, observability, and deployment best practices
- Building and maintaining LLM evaluation pipelines to assess model quality, track regressions, and support continuous improvement cycles
- Engaging in code review, pair programming and architecture discussions with other members of the team
- Strong programming skills (Python, Swift, Go or other language)
- Experience with MLOps/LLMOps toolkits and frameworks
- Comprehensive knowledge and hands‑on experience with LLM evaluations
- A learning attitude to continuously improve self and team
- BS, MS or PhD in Computer Science, Artificial Intelligence, or Machine Learning (or equivalent experience)
- Experience with: Xcode, Swift and developing for Apple’s platforms
- Familiarity with on‑device LLMs
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.
Applied Machine Learning Engineer - Developer Publications employer: Apple
Contact Detail:
Apple Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Machine Learning Engineer - Developer Publications
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Apple. Use LinkedIn or even Twitter to connect with current employees and ask them about their experiences. A friendly chat can sometimes lead to job opportunities!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to machine learning and LLMs. This could be anything from GitHub repositories to personal blogs explaining your work. It’s a great way to demonstrate your expertise and passion.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding of MLOps/LLMOps. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key, so make sure you know your stuff!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Apple team. So, get that application in and let’s make some magic happen!
We think you need these skills to ace Applied Machine Learning Engineer - Developer Publications
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming skills and experience with MLOps/LLMOps in your application. We want to see how your background aligns with the role, so don’t hold back on showcasing your expertise!
Tailor Your Application: Take a moment to customise your application for this specific role. Mention your experience with large language models and any relevant projects you've worked on. This helps us see how you fit into our team!
Be Yourself: We value diversity and individuality at StudySmarter. Don’t be afraid to let your personality shine through in your application. Share your unique perspective and experiences that make you a great fit for our team.
Apply Through Our Website: For the best chance of success, make sure to apply directly through our website. It’s the easiest way for us to review your application and get you one step closer to joining our amazing team!
How to prepare for a job interview at Apple
✨Know Your LLMs
Make sure you brush up on your knowledge of large language models. Be prepared to discuss their architecture, evaluation methods, and any recent advancements in the field. This will show that you're not just familiar with the concepts but are genuinely passionate about them.
✨Showcase Your Coding Skills
Since strong programming skills are a must, be ready to demonstrate your proficiency in Python, Swift, or Go. You might be asked to solve coding problems on the spot, so practice common algorithms and data structures beforehand to keep your skills sharp.
✨Engage in Team Dynamics
Apple values collaboration, so be prepared to discuss how you've worked in teams before. Share examples of code reviews, pair programming, or architecture discussions you've participated in. Highlighting your ability to work well with others will resonate with their team-oriented culture.
✨Emphasise Continuous Learning
Demonstrate your learning attitude by discussing how you've kept up with industry trends or improved your skills over time. Mention any relevant courses, certifications, or personal projects that showcase your commitment to growth in the machine learning space.