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- Tasks: Guide AI/ML use cases, build models, and enhance AI literacy in a biopharma setting.
- Company: Leading biopharma company in Greater London with a focus on innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Dynamic work environment with a focus on collaboration and career advancement.
- Why this job: Make a real impact in healthcare by leveraging cutting-edge AI technologies.
- Qualifications: Bachelor's degree and 3+ years in machine learning, with strong Python skills.
The predicted salary is between 48000 - 72000 £ per year.
A leading biopharma company in Greater London is seeking an experienced Machine Learning Specialist to work at the intersection of business needs and technical capability. This role involves providing guidance on AI/ML use cases, building models, and enhancing AI literacy within the organization.
The ideal candidate will have a Bachelor's degree in a relevant field and over three years of experience in developing and deploying machine learning models. Strong expertise in Python and cloud platforms is required, along with experience in healthcare applications.
Senior Applied AI Engineer — Pharma ML & Deployments in London employer: GlaxoSmithKline
Contact Detail:
GlaxoSmithKline Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Applied AI Engineer — Pharma ML & Deployments in London
✨Tip Number 1
Network like a pro! Reach out to people in the biopharma industry on LinkedIn or at local meetups. 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 machine learning projects, especially those related to healthcare. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common AI/ML questions and case studies. Practice explaining your thought process clearly, as communication is key in bridging business needs with technical solutions.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect 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 Senior Applied AI Engineer — Pharma ML & Deployments in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in developing and deploying machine learning models, especially in healthcare. 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! Use it to explain why you’re passionate about AI in pharma and how your background makes you the perfect fit for this role. We love seeing genuine enthusiasm!
Showcase Your Technical Skills: Since strong expertise in Python and cloud platforms is a must, make sure to mention specific tools and technologies you’ve worked with. We’re keen to know how you’ve applied these skills in real-world scenarios.
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 GlaxoSmithKline
✨Know Your AI/ML Stuff
Make sure you brush up on your machine learning concepts and applications, especially in the pharma sector. Be ready to discuss specific projects you've worked on, the models you've built, and how they addressed business needs.
✨Showcase Your Python Skills
Since strong expertise in Python is a must, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot or explain your thought process behind a particular model implementation.
✨Understand the Business Side
This role sits at the intersection of business and tech, so be prepared to discuss how your technical solutions can drive business outcomes. Think about how you've previously aligned AI/ML projects with business goals.
✨Familiarise Yourself with Cloud Platforms
As cloud experience is essential, make sure you know the ins and outs of the platforms you've used. Be ready to talk about how you've deployed models in the cloud and any challenges you faced during the process.