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- Tasks: Lead the development of cutting-edge AI systems for diverse clients.
- Company: Join Faculty, a leader in responsible AI innovation since 2014.
- Benefits: Enjoy unlimited leave, private healthcare, and flexible working options.
- Why this job: Empower yourself to shape the future of AI and make a real impact.
- Qualifications: Experience with ML lifecycle, Python, and cloud platforms required.
- Other info: Diverse team culture with opportunities for mentorship and growth.
The predicted salary is between 43200 - 72000 ÂŁ per year.
Join to apply for the Senior Machine Learning Engineer role at Faculty. We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human‑centric AI. Our clients span government, finance, retail, energy, life sciences and defence. AI is an epoch‑defining technology – join a company where you’ll be empowered to envision its most powerful applications and to make them happen.
About the Role
As a Senior Machine Learning Engineer, you’ll lead the development and deployment of cutting‑edge AI systems for our diverse clients. This ambitious, cross‑functional role requires technical expertise, engineering leadership and confident client‑facing skills. You’ll design, build and deploy scalable, production‑grade ML software and infrastructure that meets rigorous operational and ethical standards.
What You’ll Be Doing
- Leading technical scoping and architectural decisions for high‑impact ML systems
- Designing and building production‑grade ML software, tools, and scalable infrastructure
- Defining and implementing best practices and standards for deploying machine learning at scale across the business
- Collaborating with engineers, data scientists, product managers and commercial teams to solve critical client challenges and leverage opportunities
- Acting as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies
- Mentoring and developing junior engineers, actively shaping our team's engineering culture and technical depth
Who We’re Looking For
- Deep understanding of the full ML lifecycle and significant experience operationalising models built with TensorFlow or PyTorch
- Strong software engineering background with robust Python skills, focusing on building reusable systems
- Hands‑on experience with cloud platforms (AWS, Azure, GCP) – architecture, security and infrastructure
- Extensive experience with container and orchestration tools such as Docker and Kubernetes to build and manage applications at scale
- Thrives in fast‑paced, high‑growth environments, demonstrating ownership and autonomy in driving projects to completion
- Exceptional communication skills, confidently guiding both technical teams and senior, non‑technical stakeholders
Our Recruitment Ethos
We aim to grow the best team – not the most similar one. Diversity nurtures diverse thinking, strengthening our pursuit of truth. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Some Of Our Standout Benefits
- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family‑Friendly Flexibility & Flexible working
- Sanctus Coaching
- Hybrid Working (2 days in our Old Street office, London)
If you don’t feel you meet all the requirements but are excited by the role, please apply or email for a confidential chat – we’re open to part‑time or condensed hours.
Senior Machine Learning Engineer in England employer: Faculty
Contact Detail:
Faculty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in England
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Faculty. A personal introduction can make all the difference in getting your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those using TensorFlow or PyTorch. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Tip Number 4
Don’t hesitate to apply through our website! Even if you don’t tick every box, your enthusiasm and unique background could be just what we’re looking for. We value diverse perspectives!
We think you need these skills to ace Senior Machine Learning Engineer in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Machine Learning Engineer role. Highlight your expertise in ML lifecycle, Python, and cloud platforms to catch our eye!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI and how you can contribute to our mission at Faculty. Share specific examples of your past projects that align with what we do.
Showcase Your Technical Skills: Don’t just list your skills; demonstrate them! Include links to your GitHub or any projects that showcase your experience with TensorFlow, PyTorch, or cloud infrastructure. We love seeing your work!
Apply Through Our Website: We encourage you to apply directly 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 updates!
How to prepare for a job interview at Faculty
✨Know Your ML Stuff
Make sure you brush up on the full machine learning lifecycle, especially with TensorFlow and PyTorch. Be ready to discuss your past projects in detail, focusing on how you operationalised models and the impact they had.
✨Show Off Your Engineering Skills
Highlight your software engineering background, particularly your Python skills. Prepare examples of reusable systems you've built and be ready to explain your approach to coding and best practices in software development.
✨Cloud Knowledge is Key
Familiarise yourself with cloud platforms like AWS, Azure, or GCP. Be prepared to discuss your experience with architecture, security, and infrastructure, as well as how you've used container tools like Docker and Kubernetes in your projects.
✨Communicate Like a Pro
Since this role involves guiding both technical teams and non-technical stakeholders, practice explaining complex concepts in simple terms. Think of examples where you've successfully communicated technical information to clients or team members.
