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

At a Glance

  • Tasks: Lead ML/AI strategies and drive innovation across teams to enhance customer service.
  • Company: Join Capital One, a leader in data and AI transformation.
  • Benefits: Competitive salary, flexible working, generous holiday, and professional development opportunities.
  • Other info: Diverse and inclusive workplace with strong career progression and support networks.
  • 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 80000 - 100000 £ per year.

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.

Staff Software Engineer - Machine Learning employer: Capital One

At Capital One, we pride ourselves on being an exceptional employer, particularly for our Staff Software Engineer - Machine Learning role based in London. Our hybrid working model promotes flexibility and collaboration, while our commitment to employee growth is evident through extensive training programmes and diverse career progression opportunities. With a focus on innovation and a supportive work culture, we offer competitive benefits including a generous holiday entitlement, private medical insurance, and access to inspiring facilities, making us a fantastic place to build a meaningful career.
Capital One

Contact Detail:

Capital One Recruiting Team

StudySmarter Expert Advice 🤫

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

✨Tip Number 1

Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even local tech events. You never know who might be looking for someone with your skills!

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your ML projects or contributions to open-source. This is a great way to demonstrate your expertise and passion for the field.

✨Tip Number 3

Prepare for those interviews! Research common ML/AI interview questions and practice your answers. Be ready to discuss your past experiences and how they relate to the role you're applying for.

✨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, we love seeing candidates who are genuinely interested in joining our 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
Data Pipelines
Model Serving
Business Acumen

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with ML/AI systems and Python. We want to see how your skills align with our mission to drive innovation and efficiency!

Showcase Your Projects: Include specific examples of past projects where you've led ML engineering efforts or influenced technical strategies. We love seeing real-world applications of your expertise, so don’t hold back!

Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, especially when discussing complex topics like MLOps and cloud-native architectures.

Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity!

How to prepare for a job interview at Capital One

✨Know Your ML/AI Stuff

Make sure you brush up on your knowledge of machine learning frameworks like PyTorch and TensorFlow. Be ready to discuss your experience with MLOps and cloud platforms, as these are crucial for the role. Prepare examples of how you've led ML initiatives and the impact they had.

✨Showcase Your Leadership Skills

This role requires strong technical leadership, so think about times when you've influenced teams without direct authority. Be prepared to share specific examples of how you've driven alignment across multiple teams and contributed to a shared technical vision.

✨Understand the Business Side

Capital One is looking for someone who can translate complex ML concepts into business value. Familiarise yourself with how AI can drive efficiency and service customers better. Think of ways you've done this in past roles and be ready to discuss them.

✨Prepare for Technical Questions

Expect deep technical questions about ML/AI systems design and best practices. Brush up on your understanding of responsible AI practices and be ready to discuss how you've managed technical debt in previous projects. Practising coding problems related to Python and ML could also give you an edge.

Staff Software Engineer - Machine Learning
Capital One

Land your dream job quicker with Premium

You’re marked as a top applicant with our partner companies
Individual CV and cover letter feedback including tailoring to specific job roles
Be among the first applications for new jobs with our AI application
1:1 support and career advice from our career coaches
Go Premium

Money-back if you don't land a job in 6-months

>