Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Director, Machine Learning Centre of Excellence | London, UK

HSBC
London
1 week ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Director, Machine Learning Centre of Excellence

Group AI Management and Strategy (AIMS) team is responsible for developing and implementing Group-wide strategic programs across HSBC aimed at accelerating the commercialisation and delivery of Artificial Intelligence / Machine Learning (AI/ML) across HSBC. Key areas of focus include responsible development practices, common platforms and capabilities, AI technology enablement, governance, and the Group-wide AI Strategy.

In this strategic role, you will join a growing team to lead the Machine Learning Centre of Excellence (ML-COE). This role is critical for HSBC to deliver complex AI/ML use cases that generate value within our Group Businesses and Functions (GB/GFs). You will oversee use case prioritization, delivery, assurance, and contribute to shaping the team through hiring and development initiatives. Building trusted relationships with AI developers and business units will be essential.

Your duties will include:

  1. Use Case Management: Prioritising and managing AI/ML use cases to align with business objectives and maximize value.
  2. Delivery Oversight: Leading AI/ML project execution, ensuring timely and quality delivery.
  3. Team Development: Driving hiring and team-building efforts, mentoring AI Data Scientists, Engineers, and Researchers.
  4. Strategic Partnership: Establishing and maintaining relationships with Group Businesses and Functions as a trusted AI partner.
  5. Collaboration: Working closely with AI developers to foster a collaborative environment.
  6. Governance and Assurance: Ensuring adherence to governance frameworks and assurance processes.
  7. Industry Trends: Staying updated on AI research and integrating relevant advancements into projects.
  8. Compliance: Ensuring all AI activities comply with HSBC Responsible AI standards and regulatory requirements.

Skills required include:

Technical:

  • AI research and project management
  • Experience with AI frameworks like TensorFlow, PyTorch
  • Knowledge of AI/ML algorithms, neural networks, NLP, deep learning
  • Understanding of financial industry regulations (GDPR, CCPA, etc.)
  • Relationship and stakeholder management

Behavioral:

  • Analytical thinking
  • Business partnering
  • Customer orientation
  • Outcome focus
  • Problem-solving
  • Team management

Cognitive:

  • Attention management
  • Critical thinking
  • Collaboration

This role is based in London on a hybrid basis.

HSBC values diversity and inclusion. We welcome candidates from all backgrounds and are committed to accessible recruitment processes. If you require accommodations, please contact our Recruitment Helpdesk at or .


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.