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For Companies At a Glance
- Tasks: Lead a team to develop software and integrate machine learning into financial products.
- Company: Join Capital One, a leading tech company transforming banking with innovation.
- Benefits: Enjoy competitive salary, performance bonuses, and access to top-notch facilities.
- Other info: Hybrid work model with opportunities for personal and professional growth.
- Why this job: Make a real impact by shaping the future of finance with cutting-edge technology.
- Qualifications: Experience in software engineering and leadership, with knowledge of AI and cloud environments.
The predicted salary is between 80000 - 100000 £ per year.
About this role
We are looking for a Software Engineering Manager who brings a solid foundation in modern development and some experience with Machine Learning environments. You’ll lead and grow a team that builds the core software powering our data-driven financial products, ensuring our models are integrated into seamless, consumer-facing experiences.
What you’ll do
- Lead & Scale: Support a cross-functional group of engineers to design, develop, and integrate software features that are vital to the lives of credit card consumers.
- Nurture Talent: Coach and nurture your engineers, including those working on ML integration to achieve their technical, business, and personal goals.
- Bridge the Gap: Collaborate with Product Managers and Data Scientists to ensure ML models are effectively integrated into our production software.
- Build Robust Systems: Oversee the development of platforms that are performant, secure, and capable of handling the unique deployment needs of AI-powered features.
- Optimize Delivery: Enhance engineering and agile processes, ensuring that model updates and software releases move in sync.
What we’re looking for
- Leadership Excellence: Proven experience leading and supporting software engineering teams to achieve business goals.
- Technical Breadth: Excellent knowledge of RESTful API development in modern languages (Java, Python, or .Net) and experience with Cloud environments (AWS or Azure).
- AI Awareness: You aren't necessarily a researcher, but you have expectations of how AI fits into the stack. You understand the basics of model inference, data requirements, and how to manage the non-deterministic nature of AI.
- Strategic Thinking: Comfortable making technical trade-offs between the need for rapid experimentation and long-term architectural stability.
- Collaborative Mindset: Ability to communicate effectively across engineering teams to maximize inner-sourcing and reduce technical debt.
What you’ll get to learn
- ML Integration at Scale: How to take machine learning models out of the lab and into a high-concurrency production environment.
- Regulated AI: Navigating the complexities of fairness and transparency in a regulated financial landscape.
- Cloud Evolution: Deepening your expertise in AWS/Cloud native tools that support modern intelligent applications.
Where and how you'll work
This is a permanent position based in either our London or Nottingham offices. We have a hybrid working model. You'll be based in the office 3 days a week (Tuesdays, Wednesdays, and Thursdays) to foster team connection and collaboration.
What’s in it for you
- Innovation Time: We give you 10% of your time to work on cutting-edge projects whether that’s exploring new AI frameworks or building internal tools.
- Growth: Access to Capital One University and external training to help you grow as both a leader and a technical strategist.
- Total Reward: Competitive salary, performance bonus, and immediate access to core benefits (pension, private medical, and generous holiday).
- World-Class Facilities: From our Nottingham gym and music rooms to our London rooftop running track and premium coffee bars.
Our Commitment to Diversity
We pride ourselves on hiring the best people, not the same people. We partner with organisations like Women in Tech and Stonewall to ensure we build teams that reflect the customers we serve. We offer a host of internal networks including REACH (Race Equality and Culture Heritage), OutFront (LGBTQ support), and Mind Your Mind. Capital One is committed to diversity in the workplace.
If you require a reasonable adjustment, please contact ukrecruitment@capitalone.com. All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com.
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Who We Are
At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding. Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.
Engineering Manager – Software & ML in London employer: Employer near you
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StudySmarter Expert Advice 🤫
We think this is how you could land Engineering Manager – Software & ML in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for those interviews! Research the company and its culture, and be ready to discuss how your experience aligns with their needs. Practise common interview questions and think about how you can showcase your leadership skills.
✨Tip Number 3
Show off your projects! If you've worked on any relevant software or ML projects, make sure to highlight them during interviews. Bring a portfolio or share links to your work to demonstrate your expertise.
✨Tip Number 4
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 our team at Capital One.
We think you need these skills to ace Engineering Manager – Software & ML in London
Some tips for your application 🫡
Show Your Leadership Skills: When writing your application, make sure to highlight your experience in leading software engineering teams. We want to see how you've nurtured talent and supported your team in achieving their goals.
Demonstrate Technical Knowledge: Be specific about your technical skills, especially in RESTful API development and cloud environments like AWS or Azure. We love seeing candidates who can bridge the gap between software and machine learning.
Communicate Your Collaborative Mindset: We value collaboration, so share examples of how you've worked with product managers and data scientists. Show us how you’ve effectively communicated across teams to reduce technical debt and enhance project outcomes.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and get you started on this exciting journey with us at StudySmarter.
How to prepare for a job interview at Employer near you
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of RESTful API development and the programming languages mentioned in the job description, like Java, Python, or .Net. Familiarise yourself with cloud environments such as AWS or Azure, as these are crucial for the role.
✨Showcase Your Leadership Skills
Prepare examples that highlight your experience in leading software engineering teams. Think about how you've nurtured talent and supported your team in achieving their goals. Be ready to discuss specific instances where your leadership made a difference.
✨Understand AI Integration
Since the role involves machine learning, it’s important to demonstrate your understanding of how AI fits into software development. Brush up on model inference basics and be prepared to discuss how you would manage the complexities of integrating ML models into production.
✨Communicate Collaboratively
This position requires effective communication across various teams. Think of examples where you’ve successfully collaborated with product managers or data scientists. Highlight your ability to bridge gaps and reduce technical debt through teamwork.