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- Tasks: Lead a team to build cutting-edge ML infrastructure for biotech research.
- Company: Join a pioneering biotech firm at the forefront of AI and biology.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact in AI-driven biology and support groundbreaking research.
- Qualifications: 10+ years in leadership with strong ML infrastructure and software engineering skills.
- Other info: Dynamic role with hands-on leadership and direct influence on innovative projects.
The predicted salary is between 72000 - 108000 £ per year.
You will build and lead a high-impact team responsible for large-scale training systems, data pipelines, and research platforms that support foundation model development and rapid experimentation. We’re working with a brilliant Biotech who are building AI systems at the intersection of machine learning and biology—and we’re looking for a senior engineering leader to own the infrastructure that makes research move fast.
This role is about enabling scientists: making large-scale model training simple, data access seamless, and experimentation reproducible by default. You’ll lead an elite platform team that powers foundation models trained on large, complex biological datasets (genomics, multi-omics, clinical).
What you’ll do:
- Build and scale distributed training infrastructure for large ML models
- Own data pipelines from raw biological data → ML-ready formats
- Create researcher-friendly platforms for experiments, tracking, and reproducibility
- Manage cloud + on‑prem compute and keep costs under control
- Lead and grow a high-impact team of ML/platform engineers
Who you are:
- 5+ years building ML or research infrastructure
- 10 Years commercial leadership experience
- Deep experience with distributed training (PyTorch, DeepSpeed, Ray, etc.)
- Strong software engineering + cloud/Kubernetes background
- Comfortable in fast-moving research environments
- Bonus: experience with scientific or biological data
This is a hands‑on leadership role with real ownership and direct impact on how AI‑driven biology gets done.
Location: London
Company: confidential (details shared during process)
Get in touch with the team @KEMIO Consulting to find out more or schedule a confidential discussion.
Head of MLOps and AI Infrastructure employer: KEMIO Consulting
Contact Detail:
KEMIO Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of MLOps and AI Infrastructure
✨Tip Number 1
Network like a pro! Reach out to your connections in the biotech and AI fields. Attend meetups, webinars, or conferences where you can chat with industry leaders. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to ML infrastructure and data pipelines. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and leadership experience. Be ready to discuss how you've built and scaled systems in the past. Practice common interview questions and scenarios that relate to the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Head of MLOps and AI Infrastructure
Some tips for your application 🫡
Show Your Passion for AI and Biology: When writing your application, let your enthusiasm for AI and its intersection with biology shine through. We want to see how your experience aligns with our mission of enabling scientists and making research more efficient.
Highlight Relevant Experience: Make sure to emphasise your background in building ML infrastructure and leading teams. We’re looking for someone with a solid track record, so don’t hold back on showcasing your achievements in distributed training and cloud computing.
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the Head of MLOps and AI Infrastructure role. We appreciate when candidates take the time to connect their skills and experiences directly to what we’re looking for.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity to lead a high-impact team in a fast-paced environment.
How to prepare for a job interview at KEMIO Consulting
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like distributed training frameworks (PyTorch, DeepSpeed, Ray) and cloud infrastructure. Brush up on your software engineering skills and be ready to discuss how you've applied them in past roles.
✨Showcase Your Leadership Experience
Prepare examples that highlight your leadership style and experience managing high-impact teams. Think about specific challenges you've faced and how you’ve successfully led your team through them, especially in fast-paced research environments.
✨Understand the Biotech Landscape
Familiarise yourself with the intersection of AI and biology. Be prepared to discuss how large-scale model training can impact biotech research and how you can enable scientists to work more efficiently with data pipelines and experimentation platforms.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current projects, challenges they face in ML infrastructure, or how they envision the future of AI in their research. This not only demonstrates your enthusiasm but also helps you gauge if the company is the right fit for you.