At a Glance
- Tasks: Design and implement scalable ML systems while leading innovative AI projects.
- Company: Join a pioneering AI company transforming performance for global clients.
- Benefits: Flexible hours, competitive salary, and opportunities for professional growth.
- Other info: Opportunity for part-time work and dynamic team environment.
- Why this job: Make a real impact in AI and work with cutting-edge technologies.
- Qualifications: Expertise in cloud-native ecosystems and experience with TensorFlow or PyTorch.
The predicted salary is between 63000 - 77000 £ per year.
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. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle.
Responsibilities:
- Designing, implementing, and maintaining reliable, scalable ML systems while justifying key architectural decisions for production environments.
- Driving the development of shared libraries and infrastructure for model deployment, lifecycle management, and CI/CD pipelines.
- Leading model integration with infrastructure by creating APIs and services that enable scalable AI functionality in applications.
- Overseeing the delivery of multiple complex workstreams and defining project problems in high-risk environments.
- Ensuring reliable model performance by defining testing frameworks and model versioning systems for senior engineers to implement.
- Managing and coaching multiple individuals, setting team-wide development goals to improve technical depth and client delivery.
- Executing proactive recommendations for adopting new technologies and AI frameworks to maintain Faculty's competitive market position.
Requirements:
- You are an expert at defining technical roadmaps and managing project priorities to deliver high-stakes outcomes within high-growth environments.
- You possess mastery of cloud-native ecosystems and orchestration tools like Kubernetes to automate complex model lifecycles and robust CI/CD pipelines.
- You have a proven ability to design large-scale, AI-powered platforms and provide the technical justification for critical architectural decisions in high-risk environments.
- You bring expert-level experience in operationalising models within frameworks like TensorFlow or PyTorch to solve complex, high-impact business challenges.
- You define the engineering standards and architecture patterns for agentic systems, ensuring teams build to a consistent, production-grade bar.
- You demonstrate an exceptional ability to align multi-disciplinary technical teams with broader business objectives and evolving customer needs.
- Because of the nature of the work we do with our Government clients, you may need to be eligible for UK Developed Vetting (DV) and willing to work on site with our clients from time to time.
We are open to conversations about part-time hours.
Machine learning engineer for AI platforms employer: Faculty
At Faculty, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As the Head of Banking AI Transformation, you will have the opportunity to lead transformative projects in a rapidly evolving sector while benefiting from our commitment to employee growth through continuous learning and development. Located in a vibrant area, our team enjoys a supportive environment that values diversity and encourages meaningful contributions to the financial services landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Machine learning engineer for AI platforms
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Faculty or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Faculty.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Faculty.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Faculty that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Machine learning engineer for AI platforms
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Faculty.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Faculty and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Faculty
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Faculty uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
