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- Tasks: Lead a team to develop large-scale ML training systems and data pipelines.
- Company: Biotechnology consulting firm focused on AI-driven biological research.
- Benefits: Competitive salary, ownership in projects, and impactful work in science.
- Why this job: Make a real difference in AI research while leading a talented team.
- Qualifications: Extensive experience in ML infrastructure and distributed training systems.
- Other info: Exciting opportunity based in London with significant career growth potential.
The predicted salary is between 72000 - 108000 £ per year.
A biotechnology consulting firm is seeking a Senior Engineering Leader to oversee the development of large-scale training systems and data pipelines. This role involves leading a high-impact team, enabling scientists through seamless data access and reproducible experimentation.
Candidates should have extensive experience in ML infrastructure, commercial leadership, and distributed training systems like PyTorch. The position offers real ownership and impact in AI-driven biological research, located in London.
Head of ML Platform & AI Infrastructure employer: KEMIO Consulting
Contact Detail:
KEMIO Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of ML Platform & AI Infrastructure
✨Tip Number 1
Network like a pro! Reach out to professionals in the biotechnology and AI fields on LinkedIn. Join relevant groups and engage in discussions to get your name out there and show off your expertise.
✨Tip Number 2
Prepare for those interviews! Research common questions for senior engineering roles, especially around ML infrastructure and data pipelines. Practise your answers and be ready to showcase your leadership experience.
✨Tip Number 3
Showcase your projects! If you've worked on large-scale training systems or distributed training with PyTorch, make sure to highlight these in conversations. Real-world examples can set you apart from other candidates.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from our platform, and it gives you a better chance of standing out. Plus, it’s super easy to do!
We think you need these skills to ace Head of ML Platform & AI Infrastructure
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI and biotechnology shine through. We want to see how your experience aligns with our mission of enabling scientists and driving impactful research.
Highlight Relevant Experience: Make sure to showcase your extensive experience in ML infrastructure and distributed training systems like PyTorch. We’re looking for someone who can lead a high-impact team, so don’t hold back on your achievements!
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and how you can contribute to our team.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity in London.
How to prepare for a job interview at KEMIO Consulting
✨Know Your Tech Inside Out
Make sure you’re well-versed in ML infrastructure and distributed training systems like PyTorch. Brush up on your technical knowledge and be ready to discuss specific projects where you've implemented these technologies.
✨Showcase Leadership Experience
Prepare examples that highlight your leadership skills, especially in high-impact teams. Think about times when you enabled your team to achieve their goals or improved processes for seamless data access and reproducible experimentation.
✨Understand the Company’s Mission
Research the biotechnology consulting firm and understand their focus on AI-driven biological research. Be ready to discuss how your experience aligns with their mission and how you can contribute to their goals.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current challenges in ML infrastructure or how they envision the future of AI in their research. This demonstrates your engagement and strategic thinking.