Staff Software Engineer - Machine Learning
Staff Software Engineer - Machine Learning

Staff Software Engineer - Machine Learning

Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
Capital One UK

At a Glance

  • Tasks: Lead ML/AI strategies and drive innovation across teams to enhance customer service.
  • Company: Join Capital One, a tech-driven company transforming banking with data and AI.
  • Benefits: Enjoy competitive salary, flexible working, and extensive career development opportunities.
  • Other info: Diverse and inclusive workplace with strong support networks for all associates.
  • Why this job: Make a real impact in the AI space while collaborating with top talent.
  • Qualifications: Expertise in Python, ML engineering, and cloud platforms required.

The predicted salary is between 80000 - 100000 £ 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 (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, 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 upReach to find people from every walk of life and help them thrive with us. We have a whole host of internal networks and support groups you could be involved in, to name a few: REACH – Race Equality and Culture Heritage group focuses on representation, retention and engagement for associates from minority ethnic groups and allies OutFront – to provide LGBTQ+ support for all associates Mind Your Mind – signposting support and promoting positive mental wellbeing for all Women in Tech – promoting an inclusive environment in tech EmpowHER – network of female associates and allies focusing on developing future leaders, particularly for female talent in our industry Enabled – focused on supporting associates with disabilities and neurodiversity Capital One is committed to diversity in the workplace. 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. For technical support or questions about Capital One's recruiting process, please send an email to 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. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). 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

Staff Software Engineer - Machine Learning employer: Capital One UK

At Capital One, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London office provides a hybrid working model, allowing flexibility while ensuring strong team connections, and we invest heavily in employee development through comprehensive training programmes. With a commitment to diversity and inclusion, we create an environment where every associate can thrive and contribute to meaningful projects that transform the banking experience.
Capital One UK

Contact Detail:

Capital One UK Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff Software Engineer - Machine Learning

✨Network Like a Pro

Get out there and connect with folks in the industry! Attend meetups, webinars, or tech conferences where you can chat with other ML enthusiasts. Building relationships can open doors to opportunities that aren’t even advertised.

✨Show Off Your Skills

Don’t just tell them what you can do; show them! Create a portfolio of your projects, especially those involving Python and ML engineering. Share your GitHub link when you apply through our website to give them a taste of your work.

✨Ace the Interview

Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice common interview questions and be ready to discuss your past projects. Remember, confidence is key, so believe in your abilities!

✨Follow Up

After your interview, don’t forget to send a thank-you email! It shows your enthusiasm for the role and keeps you fresh in their minds. Plus, it’s a great chance to reiterate why you’re the perfect fit for the team.

We think you need these skills to ace Staff Software Engineer - Machine Learning

Python
ML Engineering
MLOps
Cloud-native Architectures
AWS
Azure
GCP
ML Frameworks (PyTorch, TensorFlow, scikit-learn)
Gen AI/Agentic Frameworks (LangGraph, LangChain, VectorDBs, RAG)
Responsible AI Practices
Technical Leadership
Multi-team Coordination
Technical Consultancy
Data Pipelines
Model Serving

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter for the Staff Software Engineer role. Highlight your experience with ML/AI systems and how it aligns with our mission at Capital One. We want to see how you can drive innovation and technical strategy!

Showcase Your Technical Skills: Don’t hold back on showcasing your deep expertise in Python, ML engineering, and cloud platforms. We’re looking for someone who can lead ML initiatives, so make sure to include relevant projects or achievements that demonstrate your capabilities.

Be Clear and Concise: When writing your application, keep it clear and to the point. Use straightforward language to explain your experience and how it relates to the role. We appreciate clarity and want to understand your journey without sifting through fluff!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our company culture there!

How to prepare for a job interview at Capital One UK

✨Know Your ML/AI Stuff

Make sure you brush up on your knowledge of machine learning and AI systems. Be ready to discuss your experience with frameworks like PyTorch and TensorFlow, and how you've applied them in real-world scenarios. This is your chance to showcase your technical expertise!

✨Showcase Leadership Skills

Since the role involves leading ML engineering efforts across multiple teams, be prepared to share examples of how you've influenced technical direction without direct authority. Highlight any experiences where you've successfully coordinated projects or mentored others.

✨Understand the Business Impact

Capital One is all about driving efficiency and meeting customer needs. Think about how your technical decisions have positively impacted business outcomes in the past. Be ready to explain how you can align ML/AI strategies with broader business objectives.

✨Prepare for Collaboration Questions

Collaboration is key in this role, so expect questions about how you've worked with cross-functional teams. Have examples ready that demonstrate your ability to build strong relationships with stakeholders and contribute to a shared vision.

Staff Software Engineer - Machine Learning
Capital One UK

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