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

Apply Now

Head of AI Infrastructure & Machine Learning Operations

Apex Group Ltd
Boston
18 hours ago
Create job alert

Head of AI Infrastructure & Machine Learning Operations

Join to apply for the Head of AI Infrastructure & Machine Learning Operations role at Apex Group Ltd.


The Apex Group was established in Bermuda in 2003 and is now one of the world’s largest fund administration and middle office solutions providers. Our business is unique in its ability to reach globally, service locally and provide cross-jurisdictional services. With our clients at the heart of everything we do, our hard-working team has successfully delivered on an unprecedented growth and transformation journey, and we are now represented by over circa 13,000 employees across 112 offices worldwide. Your career with us should reflect your energy and passion.


That’s why, at Apex Group, we will do more than simply ‘empower’ you. We will work to supercharge your unique skills and experience. Take the lead and we’ll give you the support you need to be at the top of your game. And we offer you the freedom to be a positive disrupter and turn big ideas into bold, industry-changing realities.


For our business, for clients, and for you


Role Location

Role Location: Greater Boston Area


Reports To: Chief AI and Data Science Officer


We are seeking an ambitious and visionary Head of AI Infrastructure & Machine Learning Ops to join our leadership team and play a critical role in scaling the infrastructure, tooling, and deployment capabilities for AI and ML systems across the Apex Group. Reporting directly to the Chief AI and Data Science Officer, this is a senior strategic appointment with global scope. The successful candidate will be responsible for building secure, scalable, and compliant platforms to accelerate AI innovation and ensure operational excellence in a highly regulated financial services environment.


Key Responsibilities


  • Establish a scalable AI runtime environment to support rapid prototyping and early deployment of LLM agents and agentic workflows.
  • Design and implement a robust MLOps stack with model versioning, CI/CD pipelines, and automated monitoring for operational resilience.
  • Build secure, compliant AI development and deployment architectures while aligning with AI governance framework.
  • Collaborate cross-functionally to ensure infrastructure meets the evolving needs.


Required Skills and Qualifications


  • Proven leadership in designing scalable, cloud-native or hybrid AI/ML platforms that support experimentation and secure enterprise deployment.
  • Deep expertise in MLOps strategy and execution, including end-to-end pipelines, CI/CD, model versioning, and retraining workflows.
  • Hands-on experience with model deployment and runtime management across varied environments (batch, real-time, REST, edge), using tools like MLflow, SageMaker, Databricks, or other equivalent.
  • Strong background in monitoring, observability, and incident response — including drift detection, fairness tracking, latency alerts, and recovery protocols.
  • Skilled in building secure, compliant AI infrastructure aligned with regulatory standards (e.g., GDPR, EU AI Act).


Preferred Personal Attributes


  • Strategic thinker with strong operational and technical execution capabilities.
  • passionate about responsible AI, platform resilience, and infrastructure innovation.
  • Comfortable working in high-ambiguity, fast-paced startup-like environments.
  • Collaborative leader with strong interpersonal and communication skills.
  • High integrity, accountability, and a commitment to ethical technology adoption.


What you will expose


  • Be part of a dynamic and fast-paced team that makes a genuine impact on the success of the entire organisation.
  • Opportunity to work with a diverse, agile, and global team.
  • Exposure to all aspects of the business, cross-jurisdiction.
  • A genuinely unique opportunity to be part of an expanding large global business.
  • Competitive remuneration in line with skills and experience.
  • Training and development opportunities.


We pride ourselves in our commitment to fostering a connected and inclusive culture; all our opportunities at Apex have five (5) days in office requirement.


Additional information

We are an equal opportunity employer and ensure that no applicant is subject to less favourable treatment on the grounds of gender, gender identity, marital status, race, colour, nationality, ethnicity, age, sexual orientation, socio-economic, responsibilities for dependants, physical or mental disability. Any hiring decision are made on the basis of skills, qualifications and experiences.


We measure our success as a business, not only by delivering great products and services and continually increasing our assets under administration and market share, but also by how we positively impact people, society, and the planet.


For more information on our commitment to Corporate Social Responsibility (CSR) please visit our CSR policy.


Disclaimer: Unsolicited CVs sent to Apex (Talent Acquisition Team or Hiring Managers) by recruitment agencies will not be accepted for this position. Apex operates a direct sourcing model and where agency assistance is required, the Talent Acquisition team will engage directly with our exclusive recruitment partners.


Seniority level


  • Executive


Employment type


  • Full-time


Job function


  • Engineering and Information Technology


#J-18808-Ljbffr

Related Jobs

View all jobs

Executive Director / Principal Machine Learning Engineer

Principal Machine Learning Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer

Head of Data Science

Junior Data Scientist

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.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.