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- Tasks: Develop innovative AI solutions to boost clinical trial success rates.
- Company: Leading life sciences company in Greater London with a focus on health tech.
- Benefits: Competitive salary and excellent benefits package.
- Why this job: Drive real transformation in drug development with cutting-edge AI technologies.
- Qualifications: Ph.D. and expertise in machine learning, deep learning, and cloud technologies.
- Other info: Hands-on role with opportunities for impactful work in health tech.
The predicted salary is between 60000 - 84000 £ per year.
A leading life sciences company in Greater London is looking for a Principal AI&ML Engineer to develop innovative AI solutions that enhance clinical trial success rates. This hands-on role requires strong coding skills and expertise in machine learning, deep learning, and cloud technologies. The successful candidate will have a Ph.D. and experience in applied AI systems, driving real transformation in drug development. Competitive salary and excellent benefits are offered.
Principal AI & ML Engineer — Health Tech & GenAI Leader employer: AstraZeneca
Contact Detail:
AstraZeneca Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal AI & ML Engineer — Health Tech & GenAI Leader
✨Tip Number 1
Network like a pro! Reach out to professionals in the health tech and AI space 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 AI and ML projects, especially those related to clinical trials or drug development. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your coding skills and understanding the latest trends in AI and machine learning. Be ready to discuss how your work can drive transformation in drug development.
✨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 ensure your application gets seen by the right people.
We think you need these skills to ace Principal AI & ML Engineer — Health Tech & GenAI Leader
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your coding skills and expertise in machine learning and deep learning. We want to see how your experience aligns with the innovative AI solutions we’re looking to develop.
Tailor Your Application: Don’t just send a generic application! Customise your CV and cover letter to reflect how your background and Ph.D. experience can drive transformation in drug development. We love seeing candidates who take the time to connect their skills to our mission.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and passion for the role.
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!
How to prepare for a job interview at AstraZeneca
✨Know Your AI Inside Out
Make sure you brush up on the latest trends and breakthroughs in AI and machine learning, especially as they relate to health tech. Be prepared to discuss your previous projects and how they’ve contributed to clinical trial success rates.
✨Showcase Your Coding Skills
Since this role requires strong coding skills, be ready to demonstrate your proficiency. Practice coding challenges related to machine learning algorithms and be prepared to explain your thought process during the interview.
✨Understand Cloud Technologies
Familiarise yourself with cloud platforms commonly used in AI development, such as AWS, Azure, or Google Cloud. Be ready to discuss how you've leveraged these technologies in past projects to drive transformation in drug development.
✨Prepare for Behavioural Questions
Expect questions that assess your leadership and teamwork abilities, especially in a hands-on role. Think of examples where you’ve led a project or collaborated with cross-functional teams to achieve a common goal in AI applications.