At a Glance
- Tasks: Lead a team to develop software and integrate machine learning into financial products.
- Company: Join a forward-thinking tech company focused on innovation and collaboration.
- Benefits: Competitive salary, performance bonuses, and access to top-notch facilities.
- Other info: Enjoy a hybrid work model and opportunities for personal and professional growth.
- Why this job: Make an impact by integrating AI in real-world applications while nurturing talent.
- Qualifications: Experience in leading teams and knowledge of modern programming languages and cloud environments.
The predicted salary is between 70000 - 90000 € per year.
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.
Responsibilities
- 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.
Qualifications
- 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 understand how AI fits into the stack, 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.
Benefits and Learning Opportunities
- ML Integration at Scale: Take machine learning models out of the lab and into a high‑concurrency production environment.
- Regulated AI: Navigate the complexities of fairness and transparency in a regulated financial landscape.
- Cloud Evolution: Deepen your expertise in AWS/Cloud native tools that support modern intelligent applications.
- Innovation Time: You’ll receive 10% of your time to work on cutting‑edge projects such as new AI frameworks or building internal tools.
- Growth: Access to Capital One University and external training to 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: Nottingham gym, music rooms, London rooftop running track and premium coffee bars.
Location and Working Model
This is a permanent position based in either our London or Nottingham offices. We operate a hybrid working model, with you based in the office three days a week (Tuesdays, Wednesdays, and Thursdays) to foster team connection and collaboration.
Commitment to Diversity and Inclusion
Capital One is committed to diversity in the workplace. We partner with organisations such as Women in Tech and Stonewall to build teams that reflect our customers. Internal networks include REACH (Race Equality and Culture Heritage), OutFront (LGBTQ+ support), and Mind Your Mind.
Legal and Accessibility Statement
If you require a reasonable adjustment, please contact. All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment.
Engineering Manager - Software & ML employer: Richard Fairbank, Capital One
At Capital One, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through access to extensive training programs and the opportunity to work on cutting-edge machine learning projects in a supportive environment. With world-class facilities in both London and Nottingham, along with a hybrid working model, we ensure our team members enjoy a balanced and rewarding work experience.
Contact Detail:
Richard Fairbank, Capital One Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Engineering Manager - Software & ML
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or at industry events. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills and understanding of ML integration. We recommend doing mock interviews with friends or using online platforms to get comfortable with common questions.
✨Tip Number 3
Showcase your leadership style! Be ready to discuss how you've nurtured talent in your previous roles. Share specific examples of how you’ve helped your team grow and succeed.
✨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 our team.
We think you need these skills to ace Engineering Manager - Software & ML
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Engineering Manager role. Highlight your leadership experience and any relevant technical expertise, especially in software development and machine learning.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about this role and how you can contribute to our team. Share specific examples of how you've led teams or integrated ML into projects, as this will help us see your fit for the position.
Showcase Your Technical Skills:Don’t shy away from detailing your technical knowledge in RESTful APIs, cloud environments, and AI awareness. We want to know how you’ve applied these skills in real-world scenarios, so be specific!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture!
How to prepare for a job interview at Richard Fairbank, Capital One
✨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 will likely come up during technical discussions.
✨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 you’ve bridged gaps between teams, especially with Product Managers and Data Scientists.
✨Understand AI Integration
Even if you're not a researcher, it's crucial to demonstrate your understanding of how AI fits into software development. Brush up on the basics of model inference and data requirements, and be prepared to discuss how you would manage the non-deterministic nature of AI in production.
✨Emphasise Collaboration
Highlight your ability to communicate effectively across different engineering teams. Prepare to discuss how you've maximised inner-sourcing and reduced technical debt in previous roles. This will show that you can foster a collaborative mindset, which is key for this position.
