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- Tasks: Lead the development of AI systems for drug discovery and clinical development.
- Company: Join Faculty, a leader in Applied AI and Decision Intelligence.
- Benefits: Enjoy unlimited annual leave, private healthcare, and a dynamic work environment.
- Other info: Be part of a prestigious team recognised by Gartner with exciting growth opportunities.
- Why this job: Make a real impact on healthcare by accelerating life-changing therapies.
- Qualifications: Extensive experience in machine learning, cloud architecture, and technical leadership.
The predicted salary is between 80000 - 100000 ÂŁ per year.
Company Description: Faculty - Applied AI scaleup and Decision Intelligence leader.
Job Description: 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 & Jill/External Ats
Contact Detail:
Jack & Jill/External Ats Recruiting Team
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 industry, especially those who work at Faculty or similar companies. A friendly chat can sometimes lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those that demonstrate your ability to build scalable infrastructure. This will give you an edge when discussing your experience during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your MLOps knowledge. Be ready to discuss how you've operationalised ML models and tackled challenges in cloud environments. Practice explaining complex concepts in simple terms!
✨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, it shows you’re genuinely interested in joining the team at Faculty.
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: In your application, don't shy away from showcasing your technical expertise. Mention your experience with Docker, Kubernetes, and cloud platforms like AWS, Azure, or GCP, as these are crucial for the role.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. This way, we can easily track your application and ensure it gets the attention it deserves!
How to prepare for a job interview at Jack & Jill/External Ats
✨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 audiences.
✨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 experimentation 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 background aligns with their mission to accelerate drug discovery and clinical development.