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- Tasks: Design and deploy advanced AI models for autonomous driving solutions.
- Company: Leading electric vehicle manufacturer in the UK with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a pioneering team shaping the future of autonomous vehicles.
- Qualifications: PhD or equivalent experience in AI, with expertise in PyTorch.
- Other info: Be part of a dynamic environment driving technological advancements.
The predicted salary is between 48000 - 72000 £ per year.
A leading electric vehicle manufacturer in the UK is looking for a full-time Machine Learning Engineer. The successful candidate will work on cutting-edge AI infrastructure aimed at developing state-of-the-art autonomous driving solutions.
This role includes:
- Designing and deploying large deep learning models
- Enhancing the training pipeline
It requires a strong background in PyTorch. Applicants should have a PhD or equivalent experience and deep knowledge of AI technologies.
Senior ML Engineer: AI Infrastructure for Autonomy employer: Rivian
Contact Detail:
Rivian Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer: AI Infrastructure for Autonomy
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow ML enthusiasts. 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 involving PyTorch and AI infrastructure. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your deep learning concepts and coding skills. Practice common ML problems and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Senior ML Engineer: AI Infrastructure for Autonomy
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with PyTorch and any relevant projects you've worked on. We want to see how your skills align with the cutting-edge AI infrastructure we're developing!
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect how your background fits the role of Senior ML Engineer. We love seeing candidates who take the time to connect their experience with our needs.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so make sure your achievements and experiences are easy to read and understand. No need for fluff!
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 in autonomous driving solutions!
How to prepare for a job interview at Rivian
✨Know Your Stuff
Make sure you brush up on your knowledge of PyTorch and deep learning models. Be ready to discuss your previous projects in detail, especially those related to AI infrastructure and autonomous driving. This will show that you’re not just familiar with the tech but have hands-on experience.
✨Showcase Your Problem-Solving Skills
Prepare to tackle some technical questions or case studies during the interview. Think about how you would approach designing and deploying large models or enhancing training pipelines. Practising these scenarios can help you articulate your thought process clearly.
✨Research the Company
Get to know the electric vehicle manufacturer’s mission, values, and recent developments in their AI initiatives. This will not only help you tailor your answers but also demonstrate your genuine interest in the role and the company.
✨Ask Insightful Questions
Prepare a few thoughtful questions to ask at the end of the interview. Inquire about their current projects in AI infrastructure or how they envision the future of autonomous driving. This shows that you’re engaged and thinking critically about the role.
