Senior Machine Learning Engineer

Collinson
Collinson is the global, privately-owned company dedicated to helping the world to travel with ease and confidence.

We use our expertise and products to craft customer experiences which enable some of the world’s best-known brands to acquire, engage and retain the most demanding and choice-rich customers. Our unique expertise and insight into high earning, frequent travellers allow us to create products and solutions for our clients that inspire greater customer engagement to drive more profitable relationships, enrich their travel experiences, protect what matters and assist in in times of need.

While specialising in Financial Services, Travel and Retail, we also support clients in multiple sectors. We have worked with over 90 airlines, 20 hotel groups and more than 600 financial institutions and banks, with clients including Accor Hotels, Air France KLM, American Express, British Airways, Cathay Pacific, Diners Club, Mandarin Oriental, Mastercard, Radisson Hotel Group, Sephora, Visa and Vhi.

We take our 30 years’ experience working with these kinds of household names in over 170 countries and help our clients to deliver the smarter experiences it takes to differentiate their propositions and help them win deeper devotion with their customers.

Collinson is a privately-owned entrepreneurial business with 2,000 passionate people working in 20 locations worldwide. Our solutions include Priority Pass, the world’s best known airport experiences programme, while we are also the trusted partner behind many of the leading financial services, airline and hotel brand’s reward programmes and loyalty initiatives.

Purpose of the job

As a Machine Learning (ML) Engineer at Collinson, you will play a critical role in driving the development of cloud-based machine learning pipelines for data-driven products and services. Your responsibilities will include collecting data from various business units and leveraging a centralized data platform to product ionize analytics and machine learning workflows. Additionally, you will be expected to provide analytical expertise across the Collinson group, ensuring the implementation of cloud-based solutions that meet the needs of both internal and external clients from across Collinson's global footprint.

As an innovator, you will be tasked with bringing fresh ideas to the team and continuously exploring new and modern engineering frameworks to enhance the overall offerings of the Collinson group. A key aspect of this role will also be to collaborate with the data platform team to integrate with the ML platform, and to support the growth and development of the team's ML skillset.

Also, it will be essential for you to be able to identify and resolve issues that arise, ensuring the quality and quantity of work produced by the team is always maximized. This will require a combination of technical expertise, problem-solving skills, and the ability to effectively communicate and collaborate with stakeholders.

Key Responsibilities

Senior ML Engineer

Job Description
The Senior ML Engineer will own the end-to-end design, development, and deployment of advanced ML and AI platforms, driving the architecture and technical direction for high-performance, scalable machine learning solutions. The role demands extensive hands-on expertise in building machine learning platforms, leveraging AWS Sage Maker, Python-based frameworks, and parallel computing for efficient large-scale data processing.

Key Responsibilities:

Lead the architecture, design, and implementation of robust, scalable, and high-performing ML and AI platforms.
Design and develop end-to-end ML workflows and pipelines using AWS Sage Maker, Python, and distributed computing technologies.
Hands-on implementation of parallel computing and distributed training methodologies to enhance the efficiency and scalability of machine learning models.
Collaborate closely with data scientists and engineers to deploy complex ML and deep learning models into mission-critical production systems.
Ensure best practices in CI/CD, containerization, orchestration, and infrastructure-as-code are consistently applied across platforms.
Foster a…