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- Tasks: Lead a team to develop scalable ML systems for drug discovery.
- Company: Leading AI healthcare firm in London with a focus on innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in healthcare by driving AI innovations.
- Qualifications: Strong background in ML engineering and leadership skills.
- Other info: Collaborative environment with a focus on health innovations.
The predicted salary is between 43200 - 72000 £ per year.
A leading AI healthcare firm in London is seeking a Machine Learning Engineering Lead to drive the engineering foundations of drug discovery. You will lead a team, applying your expertise in ML and software engineering to create scalable systems, while working in a collaborative hybrid environment. The ideal candidate has a strong background in ML engineering and a passion for impactful health innovations.
ML Engineering Lead - Hybrid, Driving AI for Drug Discovery in London employer: Isomorphic Labs
Contact Detail:
Isomorphic Labs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineering Lead - Hybrid, Driving AI for Drug Discovery in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. 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 ML projects and contributions. This is your chance to demonstrate your expertise and passion for impactful health innovations, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Practice common ML engineering questions and be ready to discuss how you lead teams and drive collaboration in a hybrid environment.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our mission to revolutionise drug discovery.
We think you need these skills to ace ML Engineering Lead - Hybrid, Driving AI for Drug Discovery in London
Some tips for your application 🫡
Show Your Passion for Health Innovations: When writing your application, let us see your enthusiasm for impactful health innovations. Share any relevant experiences or projects that highlight your commitment to using ML in healthcare.
Highlight Your Leadership Skills: As a Machine Learning Engineering Lead, we want to know about your leadership style. Include examples of how you've successfully led teams and fostered collaboration in previous roles.
Be Specific About Your Technical Expertise: Make sure to detail your technical skills in ML and software engineering. We’re looking for specifics, so mention the tools and technologies you’ve worked with that are relevant to drug discovery.
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 during the process.
How to prepare for a job interview at Isomorphic Labs
✨Know Your ML Fundamentals
Brush up on your machine learning concepts and algorithms. Be ready to discuss how you've applied these in past projects, especially in healthcare or drug discovery contexts. This shows your expertise and passion for impactful health innovations.
✨Showcase Leadership Experience
Prepare examples of how you've led teams in previous roles. Highlight your ability to foster collaboration and drive projects forward. The interviewers will want to see how you can lead a team effectively in a hybrid environment.
✨Demonstrate Problem-Solving Skills
Be ready to tackle hypothetical scenarios related to drug discovery challenges. Think through your approach to building scalable systems and how you would address potential issues. This will showcase your critical thinking and engineering prowess.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's vision for AI in drug discovery and the team's current projects. This not only shows your interest but also helps you gauge if the company aligns with your career goals and values.
