At a Glance
- Tasks: Lead the design and development of advanced ML systems for drug discovery.
- Company: Innovative AI/ML firm focused on transforming human health.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make a real-world impact in health through cutting-edge machine learning.
- Qualifications: 10+ years in software and ML engineering with deep learning expertise.
- Other info: Join a diverse team at the forefront of biomedical innovation.
The predicted salary is between 80000 - 100000 £ per year.
We’re working on a retained search for a Senior Staff Machine Learning Engineer to help build the technical backbone for training foundational models on multi-omics data at scale. This is a rare opportunity to shape state‑of‑the‑art ML systems that can translate cutting‑edge research into real‑world impact in human health.
In this role, you would:
- Lead end‑to‑end architecture for flagship ML capabilities across areas such as multimodal biomedical representation learning, foundation models for health, target discovery, biomarker discovery, imaging, and genomics.
- Partner closely with research scientists to turn promising prototypes into robust, reproducible, production‑grade systems.
- Design, train, and scale advanced deep learning models, including transformers, diffusion models, GNNs, and multimodal architectures.
- Own critical MLOps, training and inference infrastructure, including monitoring, drift detection, CI/CD, and deployment reliability.
- Mentor senior engineers and scientists, helping raise the bar across design, modelling, and technical execution.
We’re keen to speak with senior candidates who bring:
- 10+ years in software and ML engineering.
- Deep hands‑on expertise in modern ML, including deep learning, generative models, self‑supervised learning, and representation learning.
- Strong experience with Python and frameworks such as PyTorch, TensorFlow, or JAX.
- A track record of building and scaling large‑scale ML systems.
- Experience in genomics, biomedical AI, or drug discovery ML, including areas such as target discovery, biomarker discovery, protein/structure, or variant effect modelling.
Preferred background includes experience across MLOps, distributed systems, GPU infrastructure, and omics data. This is a senior, high‑impact opportunity for someone who wants to work at the intersection of machine learning, computational biology, and therapeutic innovation.
KEMIO Consulting is leading this search and would welcome confidential discussions with senior candidates. Please apply directly or get in touch with Eugene at KEMIO Consulting to discuss the opportunity in more detail. KEMIO Consulting is committed to diversity and inclusivity.
Senior Staff ML Engineer in London employer: KEMIO Consulting
Contact Detail:
KEMIO Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Staff ML Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI/ML and drug discovery fields. Attend meetups, webinars, or conferences where you can chat with industry folks. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML systems and biomedical applications. This is your chance to demonstrate your expertise in deep learning and MLOps, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms, as you'll likely need to communicate with both technical and non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves from our team.
We think you need these skills to ace Senior Staff ML Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Staff ML Engineer role. Highlight your experience with deep learning, generative models, and any relevant projects in drug discovery or genomics. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI/ML in drug discovery and how your background makes you a perfect fit. We love seeing genuine enthusiasm and a clear connection to our mission.
Showcase Your Projects: If you've worked on any impressive ML projects, make sure to mention them! Whether it's building large-scale systems or innovative models, we want to know about your hands-on experience and the impact of your work.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application directly. Plus, it shows you're serious about joining our team at StudySmarter. We can't wait to hear from you!
How to prepare for a job interview at KEMIO Consulting
✨Know Your ML Stuff
Make sure you brush up on your knowledge of modern machine learning techniques, especially deep learning and generative models. Be ready to discuss your hands-on experience with frameworks like PyTorch or TensorFlow, as well as any large-scale ML systems you've built.
✨Showcase Your Projects
Prepare to talk about specific projects where you've led the architecture or implementation of ML capabilities. Highlight how you partnered with research scientists to turn prototypes into production-grade systems, and be ready to discuss the impact of your work in drug discovery or genomics.
✨MLOps is Key
Since this role involves critical MLOps infrastructure, be prepared to discuss your experience with CI/CD, monitoring, and deployment reliability. Share examples of how you've ensured the robustness and reproducibility of your ML models in a production environment.
✨Mentorship Matters
As a senior candidate, you'll likely be expected to mentor others. Think about how you've helped raise the bar for design and technical execution in your previous roles. Be ready to share your approach to mentoring and how it has positively impacted your team.