At a Glance
- Tasks: Design and build machine learning pipelines to enhance developer workflows.
- Company: Join Apple’s innovative Insight & Release Technologies team.
- Benefits: Competitive salary, inclusive culture, and opportunities for personal growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Be at the forefront of AI-driven solutions that impact millions of users.
- Qualifications: Experience in ML engineering and software development required.
The predicted salary is between 70000 - 90000 € per year.
Do you want to help define the future of delivering Apple software to customers? Join the Insight & Release Technologies team to work on new technologies that will be used to deliver Apple platforms to millions of customers. Our team has a passion for innovation and engineering and is looking for individuals with a genuine enthusiasm for collaborating with others to solve sophisticated problems with a focus on the user experience.
You will join a team working on the next generation of software release workflows that enable the software development lifecycle for an ever-growing number of platforms and teams contributing to software products. Our applications integrate with developers’ workflows to enable the software development lifecycle from integrating source code all the way to releasing Apple platforms and assets to customers. In this role, you will work on bringing AI to our developer productivity tools. You will be at the forefront of building intelligent, agentic systems that help Apple engineers write better, higher-quality code. You will collaborate closely with data, platform, and infrastructure teams to identify high-impact opportunities where ML can meaningfully improve developer workflows.
Responsibilities- Design and build machine learning pipelines. Evaluate, integrate, and optimize ML models and agentic workflows.
- Develop intelligent systems that reason over code coverage data to surface meaningful insights, prioritize under-tested areas, and recommend targeted test strategies.
- Build and improve semantic code search capabilities that allow engineers to find relevant code, patterns, and examples across large-scale internal codebases using natural language and embedding-based retrieval.
- Apply ML techniques to advance static analysis tooling, including smarter bug detection, vulnerability identification, and code smell classification, beyond what traditional rule-based approaches can achieve.
- Partner with platform and product teams to deeply understand engineer pain points and translate them into practical, high-impact ML solutions.
- Lead the design of generative AI solutions, optimize ML infrastructure, and guide the development of data preparation and model optimization strategies.
- Drive technical direction, facilitate alignment across organizations, and mentor engineers across the team.
- Experience in ML engineering and software development, including experience in system design, architecture, and shipping scalable software products.
- Strong software engineering fundamentals (APIs, system design, distributed systems, frameworks architecture).
- Experience leading technical project strategy and optimizing ML infrastructure.
- Experience with GenAI techniques or GenAI-related concepts.
- Bachelor's degree in Computer Science, Machine Learning, or equivalent practical experience.
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.
Senior Machine Learning Engineer, Agentic Workflows - Software Delivery employer: Apple Inc.
Apple is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for a Senior Machine Learning Engineer to thrive. Located in London, employees benefit from a dynamic work environment that prioritises personal growth, inclusivity, and cutting-edge technology, while also offering comprehensive benefits and opportunities to work on impactful projects that shape the future of software delivery. With a commitment to accessibility and diversity, Apple ensures that every team member feels valued and empowered to contribute their unique perspectives.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer, Agentic Workflows - Software Delivery
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Apple or similar companies. Use LinkedIn to connect and engage with them; you never know who might have a lead on your dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects and contributions. This is your chance to demonstrate your expertise and passion for the field, making you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. 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. Plus, it shows you’re genuinely interested in being part of our team at StudySmarter.
We think you need these skills to ace Senior Machine Learning Engineer, Agentic Workflows - Software Delivery
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Engineer role. Highlight your experience in ML engineering, system design, and any relevant projects that showcase your ability to solve complex problems.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about this role and how your background makes you a great fit. Be sure to mention your enthusiasm for collaborating with teams and your interest in advancing developer productivity through AI.
Showcase Your Projects:If you've worked on any machine learning projects or have experience with generative AI techniques, make sure to include them. We love seeing real-world applications of your skills, so don’t hold back!
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 the role. Plus, it shows your initiative and interest in joining our team!
How to prepare for a job interview at Apple Inc.
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially those relevant to software development and system design. Be ready to discuss your experience with ML pipelines and how you've optimised models in past projects.
✨Showcase Your Collaboration Skills
Since this role involves working closely with various teams, prepare examples of how you've successfully collaborated in the past. Highlight any experiences where you translated complex technical issues into practical solutions for non-technical stakeholders.
✨Prepare for Technical Questions
Expect technical questions that assess your understanding of APIs, distributed systems, and architecture. Practise explaining your thought process when solving problems, as this will demonstrate your analytical skills and approach to software engineering.
✨Demonstrate Your Passion for Innovation
Apple values innovation, so be prepared to discuss your enthusiasm for new technologies and how you've applied them in your work. Share any personal projects or research related to generative AI or intelligent systems that showcase your proactive approach.
