At a Glance
- Tasks: Lead the development of AI systems for drug discovery and clinical development.
- Company: Faculty, a leading applied AI scaleup in life sciences.
- Benefits: Unlimited annual leave, private healthcare, and a dynamic consulting environment.
- Other info: Join a prestigious team recognised by Gartner, with excellent career growth opportunities.
- Why this job: Make a real impact on healthcare by accelerating life-changing therapies with AI.
- Qualifications: Experience in machine learning, cloud architecture, and strong leadership skills.
The predicted salary is between 80000 - 100000 £ per year.
Lead the development of production-grade AI systems that optimize drug discovery and clinical development for global pharma giants and MedTech startups. You will architect end-to-end MLOps pipelines and scalable cloud infrastructure, ensuring complex models move from research to real-world healthcare impact. This is a technical leadership role driving life-changing medical innovation.
Location: London, UK
Why this role is remarkable:
- Work on mission‑critical healthcare challenges, using AI to accelerate the delivery of life‑changing therapies to patients faster than ever before.
- Join a prestigious, PhD‑heavy engineering culture recently recognized by Gartner and slated for a strategic acquisition by Accenture in early 2026.
- Benefit from a high‑variety consulting‑style environment while enjoying world‑class perks like an unlimited annual leave policy and private healthcare.
What you will do:
- Lead technical scoping and architectural decisions for high‑impact ML systems, moving models from experimentation into production‑grade software.
- Build and manage scalable infrastructure using Docker, Kubernetes, and cloud platforms like AWS, Azure, or GCP to support global operations.
- Mentor junior engineers and act as a trusted technical advisor to senior stakeholders, translating complex AI strategies into actionable engineering roadmaps.
The ideal candidate:
- Extensive experience operationalizing machine learning models at scale using Python and frameworks like TensorFlow or PyTorch within robust CI/CD workflows.
- Proven expertise in cloud architecture and container orchestration (Kubernetes/Docker) for building reliable, production‑ready infrastructure.
- Strong technical leadership skills with the ability to navigate fast‑paced environments and communicate complex engineering concepts to non‑technical client partners.
Senior Machine Learning Engineer at Faculty employer: Jack and Jill AI
Faculty is an exceptional employer, offering a unique opportunity to work at the forefront of AI in healthcare. With a prestigious, PhD-heavy engineering culture and a commitment to employee well-being through benefits like unlimited annual leave and private healthcare, Faculty fosters a collaborative environment that encourages professional growth and innovation. Located in London, this scaleup not only addresses critical healthcare challenges but also positions its employees for impactful careers in a rapidly evolving industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer at Faculty
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and healthcare sectors. Attend meetups, webinars, or conferences where you can chat with folks from Faculty or similar companies. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to healthcare. Share it on platforms like GitHub or even your own website. This gives potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for technical interviews by brushing up on your MLOps knowledge. Practice coding challenges and system design questions that focus on building scalable infrastructure. We recommend using resources like LeetCode or HackerRank to get in the zone.
✨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. So, go ahead and hit that apply button!
We think you need these skills to ace Senior Machine Learning Engineer at Faculty
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with MLOps, cloud infrastructure, and any relevant projects that showcase your skills in Python, TensorFlow, or PyTorch.
Craft a Compelling Cover Letter:Your cover letter should tell us why you're passionate about AI in healthcare. Share specific examples of how you've led technical projects or mentored others, and connect your experience to the mission of Faculty.
Showcase Your Technical Skills:Don’t just list your skills; demonstrate them! Include links to projects or GitHub repositories where we can see your work in action, especially those involving Docker, Kubernetes, or cloud platforms.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Jack and Jill AI
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, TensorFlow, and Kubernetes. Brush up on your MLOps knowledge and be ready to discuss how you've operationalised machine learning models in the past.
✨Showcase Your Leadership Skills
Since this role involves mentoring junior engineers and advising senior stakeholders, prepare examples that highlight your leadership experience. Think about times when you’ve successfully guided a team or translated complex concepts for non-technical partners.
✨Prepare for Technical Scenarios
Expect to tackle technical questions or scenarios during the interview. Practice explaining your thought process for designing scalable infrastructure and moving models from research to production. This will demonstrate your problem-solving skills and technical acumen.
✨Align with Their Mission
Faculty is focused on life-changing medical innovation, so show your passion for healthcare and AI. Be ready to discuss why you want to work in this field and how your values align with their mission to accelerate drug discovery and clinical development.
