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For Companies At a Glance
- Tasks: Lead the development of cutting-edge AI systems and mentor junior engineers.
- Company: Join Faculty, a leader in human-centric AI transforming healthcare.
- Benefits: Collaborative culture, diverse team, and opportunities for professional growth.
- Why this job: Make a real impact in healthcare by optimising life-changing therapies with AI.
- Qualifications: Experience in ML lifecycle, Python, and cloud platforms like AWS or Azure.
- Other info: Dynamic environment with brilliant minds and a focus on intellectual curiosity.
The predicted salary is between 36000 - 60000 ÂŁ per year.
About Faculty
At Faculty, we transform organisational performance through safe, impactful and human-centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world. Bringing medicine to patients is complex, expensive and high‑risk. Faculty’s Life Science team is concentrated on building AI solutions which optimise the research and commercialisation of life‑changing therapies. We partner with major pharma firms, academic research centres and MedTech start‑ups to design and deliver solutions which address critical healthcare challenges, and help to democratise health for all.
About the role
As a Senior Machine Learning Engineer, we’ll look to you to lead development and deployment of cutting‑edge AI systems for our diverse clients. You’ll design, build, and deploy scalable, production‑grade ML software and infrastructure that meets rigorous operational and ethical standards. This is an ambitious, cross‑functional role requiring a blend of technical expertise, engineering leadership, and confident client‑facing skills.
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
You understand the full ML lifecycle and have significant experience operationalising models built with frameworks like TensorFlow or PyTorch. You bring deep expertise in software engineering and strong Python skills, focusing on building robust, reusable systems. You have demonstrable hands‑on experience with cloud platforms (e.g., AWS, Azure, GCP), including architecture, security, and infrastructure. You’ve extensive experience working with container and orchestration tools such as Docker and Kubernetes to build and manage applications at scale. You thrive in fast‑paced, high‑growth environments, demonstrating ownership and autonomy in driving projects to completion. You communicate exceptionally well, confidently guiding both technical teams and senior, non‑technical stakeholders.
What we can offer you
The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.
Senior Machine Learning Engineer employer: The Rundown AI, Inc.
Contact Detail:
The Rundown AI, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with Faculty employees on LinkedIn. A personal touch can make all the difference when it comes to landing that interview.
✨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 to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and cloud platform knowledge. Practice coding challenges and be ready to discuss your past projects in detail, especially how you've tackled real-world problems.
✨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 Faculty team.
We think you need these skills to ace Senior Machine Learning Engineer
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 ML frameworks like TensorFlow or PyTorch, and don’t forget to showcase your cloud platform expertise. We want to see how your skills align with what we do at Faculty!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your background makes you a perfect fit for our team. Be sure to mention any relevant projects or experiences that demonstrate your leadership and technical skills.
Showcase Your Projects: If you’ve worked on any impressive ML projects, make sure to include them in your application. Whether it’s a personal project or something from your previous job, we love seeing real-world applications of your skills. It helps us understand your hands-on experience!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to submit all your materials in one go. Plus, it shows us you’re serious about joining the Faculty team!
How to prepare for a job interview at The Rundown AI, Inc.
✨Know Your ML Frameworks
Make sure you brush up on your knowledge of TensorFlow and PyTorch. Be ready to discuss specific projects where you've operationalised models using these frameworks, as well as any challenges you faced and how you overcame them.
✨Showcase Your Cloud Experience
Since cloud platforms like AWS, Azure, and GCP are crucial for this role, prepare to talk about your hands-on experience with them. Highlight any architectural decisions you've made and how you've ensured security and infrastructure stability in your previous projects.
✨Demonstrate Leadership Skills
As a Senior Machine Learning Engineer, you'll need to lead teams and mentor junior engineers. Think of examples where you've taken ownership of a project or guided a team through a complex problem, and be ready to share those stories.
✨Communicate Complex Ideas Simply
You’ll be acting as a trusted advisor to clients, so practice explaining technical concepts in a way that non-technical stakeholders can understand. Prepare a few examples of how you've successfully communicated complex ideas in the past.
