At a Glance
- Tasks: Lead ML/AI strategy and drive innovation across teams to enhance customer service.
- Company: Join Capital One, a leader in tech-driven financial solutions.
- Benefits: Enjoy hybrid work, competitive salary, and extensive career development opportunities.
- Other info: Inclusive culture with strong support networks for diverse talent.
- 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 70000 - 90000 β¬ per year.
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.
Qualifications
- 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.
Benefits and Working Conditions
- 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.
- 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.
Staff Software Engineer - Machine Learning employer: VELOCITY MOBILE LTD.
At Capital One, we pride ourselves on being an exceptional employer that champions innovation and collaboration in the heart of London. Our hybrid working model fosters a flexible work-life balance, while our commitment to employee development through extensive training programmes ensures that you can grow your career in a supportive environment. With a focus on diversity and inclusion, we create a workplace where every voice is valued, making it an exciting place to contribute to transformative ML/AI solutions.
StudySmarter Expert Adviceπ€«
We think this is how you could land Staff Software Engineer - Machine Learning
β¨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works at Capital One. Building relationships can open doors that a CV just can't.
β¨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML/AI projects. Whether it's a GitHub repo or a personal website, having tangible evidence of your work can really impress hiring managers and set you apart from the crowd.
β¨Tip Number 3
Prepare for those interviews! Research common ML/AI interview questions and practice your answers. We want to see how you think and solve problems, so be ready to discuss your approach to complex challenges.
β¨Tip Number 4
Apply through our website! Itβs the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our mission to transform data and AI usage at Capital One.
We think you need these skills to ace Staff Software Engineer - Machine Learning
Some tips for your application π«‘
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 excellence!
Showcase Your Technical Skills:Donβt hold back on showcasing your deep expertise in Python, ML engineering, and cloud platforms. Weβre looking for someone who can lead ML initiatives, so make sure to detail your relevant projects and achievements that demonstrate your capabilities.
Emphasise Collaboration:Since this role involves working across multiple teams, highlight your experience in collaboration and mentorship. Share examples of how you've influenced others and driven alignment towards a shared technical vision. We love seeing teamwork in action!
Apply Through Our Website:We encourage you to apply directly through our website. Itβs the best way to ensure your application gets the attention it deserves. Plus, youβll find all the details about the role and our culture there!
How to prepare for a job interview at VELOCITY MOBILE LTD.
β¨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 Python, MLOps, and cloud platforms like AWS or Azure. Prepare examples of how you've led technical initiatives and influenced teams in the past.
β¨Showcase Your Leadership Skills
This role is all about driving innovation and leading multiple teams. Think of specific instances where you've successfully coordinated efforts across teams or mentored others. Highlight your ability to advocate for best practices and how you've managed technical debt in previous projects.
β¨Understand the Business Side
It's crucial to connect your technical expertise with business objectives. Be prepared to explain how your ML/AI strategies have delivered real customer value. Show that you can translate complex concepts into language that stakeholders can understand, demonstrating your strong business acumen.
β¨Engage with the Culture
Capital One values diversity and inclusion, so be ready to discuss how you can contribute to their culture. Share your thoughts on fostering an inclusive environment in tech and any experiences you have with mentoring or supporting underrepresented groups in the industry.