At a Glance
- Tasks: Train AI models and develop deep learning systems for humanoid robots.
- Company: Humanoid, a leading UK company in robotics and AI.
- Benefits: Comprehensive healthcare, generous leave, equity options, and expert collaboration.
- Other info: Collaborative environment with opportunities to work alongside top experts.
- Why this job: Join a cutting-edge team and shape the future of robotics with AI.
- Qualifications: 3+ years in AI engineering, proficient in Python and PyTorch.
The predicted salary is between 60000 - 80000 € per year.
Humanoid, based in the UK, seeks an experienced AI Engineer to advance humanoid robot technology. The role involves training AI models, working with MLOps teams, and developing deep learning systems.
Candidates should have at least 3 years of relevant experience and be proficient in Python and PyTorch.
Benefits include comprehensive healthcare, substantial annual leave, equity options, and collaborative work with top experts in AI and robotics.
Lead Deep Learning Engineer – Robotics & Edge AI employer: Humanoid
Humanoid is an exceptional employer that fosters a collaborative and innovative work culture, where employees are encouraged to push the boundaries of AI and robotics. With comprehensive healthcare, generous annual leave, and equity options, we prioritise the well-being and growth of our team members, providing ample opportunities for professional development alongside some of the brightest minds in the industry.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Deep Learning Engineer – Robotics & Edge AI
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI and robotics field on LinkedIn. Join relevant groups and engage in discussions to get your name out there and show off your expertise.
✨Tip Number 2
Showcase your skills! Create a portfolio of your projects, especially those involving Python and PyTorch. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your deep learning concepts and MLOps practices. Practice coding challenges and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We make it easy for you to submit your application and connect with us directly. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Lead Deep Learning Engineer – Robotics & Edge AI
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in AI and deep learning, especially with Python and PyTorch. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re passionate about robotics and AI, and how your background makes you the perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects:If you've worked on any cool AI or robotics projects, make sure to mention them! We’re interested in seeing your hands-on experience, so include links or descriptions of your work that demonstrate your expertise.
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. Plus, it’s super easy!
How to prepare for a job interview at Humanoid
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and PyTorch, as these are crucial for the role. Brush up on your deep learning concepts and be ready to discuss specific projects where you've applied these technologies.
✨Showcase Your Experience
With at least 3 years of relevant experience required, prepare to share detailed examples of your work in AI and robotics. Highlight any projects where you trained AI models or collaborated with MLOps teams, as this will demonstrate your hands-on expertise.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and understanding of deep learning systems. Practice explaining complex concepts in simple terms, as this shows your ability to communicate effectively with both technical and non-technical team members.
✨Emphasise Collaboration
Since the role involves working with top experts, be ready to discuss how you’ve successfully collaborated in past projects. Share examples of teamwork, especially in cross-functional settings, to show that you can thrive in a collaborative environment.
