At a Glance
- Tasks: Lead ML/AI strategies and drive innovation across teams to enhance customer service.
- Company: Join Capital One, a leader in tech-driven financial solutions.
- Benefits: Enjoy competitive pay, flexible working, and extensive career development opportunities.
- Other info: Collaborative environment with a focus on diversity and continuous learning.
- Why this job: Shape the future of AI while making a real impact on customer experiences.
- Qualifications: Expertise in Python, ML engineering, and cloud platforms required.
The predicted salary is between 63000 - 77000 £ per year.
White Collar Factory (95009), United Kingdom, London, London Staff Software Engineer - Machine Learning About this role
We're on a mission to transform the way we use data and AI to service our customers and drive efficiency across the business.
Do you love shaping the technical landscape and driving innovation across the organisation?
Are you passionate about solving complex ML and AI challenges and supporting multiple teams toward a shared technical vision?
At Capital One, you'll be part of a community of technical leaders who drive engineering excellence, foster innovation, and deliver impactful ML/AI and Gen AI solutions that meet real customer needs.
What You'll Do
- Own and drive the ML/AI technical strategy for UK use cases, spanning multiple teams and influencing the overall technical direction for AI adoption
- Lead and coordinate ML engineering efforts across multiple teams, ensuring alignment with broader business objectives, enterprise platform capabilities, and technology strategy
- Provide technical consultancy to teams delivering AI use cases, guiding architectural decisions, solution design, and effective use of enterprise ML/AI platforms and capabilities
- Proactively identify emerging ML/AI patterns, define and evangelise best practices, and establish reusable approaches that enhance delivery of AI use cases across the business
- Drive MLOps standards and practices across teams, including CI/CD for models, automated testing, monitoring, and deployment pipelines
- Collaborate with enterprise platform and data science teams, contributing to platform capabilities where appropriate and partnering on use case delivery
- Build and maintain strong relationships with key stakeholders, including senior leadership, product owners, data science teams, and enterprise platform partners
- Represent Capital One in external ML/AI technical forums, contributing to industry discussions
- Develop and advocate for strategies to proactively manage technical debt across ML/AI systems
- Actively mentor and develop engineers, fostering a culture of continuous learning
What we're looking for
- Deep expertise in Python and ML engineering
- Deep expertise in ML/AI systems design, MLOps, and cloud-native architectures
- Track record of leading ML/AI technical initiatives across multiple teams
- Strong experience with cloud platforms (AWS, Azure, GCP)
- Experience with ML frameworks (Py Torch, Tensor Flow, scikit-learn) and Gen AI/Agentic frameworks (Lang Graph, Lang Chain, Vector DBs, RAG)
- Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems
- Experience designing and scaling low-latency, customer-facing ML/AI architectures
- Proven experience setting a multi-team ML/AI technical vision and strategy
- Strong track record of technical leadership and influence without authority
- Experience driving ML engineering standards and best practices across organisations
- Deep understanding of the full ML/AI development lifecycle, including model serving, data pipelines, and Gen AI systems
- Experience leveraging enterprise platforms to deliver business use cases at scale
- Experience of steering Communities of Practice or technical forums
- Strong business acumen and ability to translate ML/AI concepts for various audiences
- Where and how you'll work
This is a permanent position based in our London office.
We have a hybrid working model which gives you flexibility to work from our office and from home.
We're big on collaboration and connection, so you'll be based in our London office 3 days a week on Tuesdays, Wednesdays and Thursdays.
- What's in it for you
- Bring us all this - and you'll be well rewarded with a role contributing to the roadmap of an organisation committed to transformation
- We offer high performers strong and diverse career progression, investing heavily in developing great people through our Capital One University training programmes (and appropriate external providers)
- Immediate access to our core benefits including pension scheme, bonus, generous holiday entitlement and private medical insurance - with flexible benefits available including season-ticket loans, cycle to work scheme and enhanced parental leave
- Open-plan workspaces and accessible facilities designed to inspire and support you.
Our Nottingham head-office has a fully-serviced gym, subsidised restaurant, mindfulness and music rooms.
What you should know about how we recruit
We pride ourselves on hiring the best people, not the same people.
Building diverse and inclusive teams is the right thing to do and the smart thing to do.
We want to work with top talent: whoever you are, whatever you look like, wherever you come from.
We know it's about what you do, not just what you say.
That's why we make our recruitment process fair and accessible.
And we offer benefits that attract people at all ages and stages.
We also partner with organisations including the Women in Finance and Race At Work Charters, Stonewall and up Reach
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Staff Software Engineer - Machine Learning in Brighton employer: Capital One
Capital One is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. With a strong commitment to employee growth, we provide ample opportunities for professional development and leadership training, ensuring our team members thrive in their careers. The hybrid working model enhances work-life balance, making Capital One a rewarding place to contribute to meaningful projects in the global payments landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Software Engineer - Machine Learning in Brighton
✨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 Capital One 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 Capital One.
✨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 Capital One.
✨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 Capital One 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 Staff Software Engineer - Machine Learning in Brighton
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 Capital One.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Capital One 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 Capital One
✨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 Capital One 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.