Recruiter for this role:

Britney Dias

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 productionize 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.   

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 SageMaker, 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 SageMaker, 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 culture of innovation, continuous improvement, and self-service analytics across the team and organization. 

Stay abreast of latest advancements in ML and AI technologies, proactively applying new techniques and tools to deliver superior outcomes. 

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Day-to-Day Activities: 
Design, build, and maintain scalable ML platform infrastructure and tooling. 

Develop optimized machine learning models, leveraging advanced supervised and unsupervised techniques. 

Rapidly prototype and iterate on proof-of-concepts and transition successful prototypes into enterprise-grade solutions. 

Conduct comprehensive reviews and present findings clearly to technical and non-technical stakeholders. 

Continuously perform horizon scanning and research emerging ML trends, tools, and methodologies. 

  
Knowledge and Skills: 
Essential: 
Deep expertise in designing and deploying ML/AI platforms, specifically using AWS SageMaker. 

Strong proficiency in Python and its ecosystem (e.g., TensorFlow, PyTorch, scikit-learn). 

Extensive hands-on experience with parallel computing frameworks and distributed processing. 

Proficient in SQL, ETL, data warehousing, and data modeling techniques. 

Thorough understanding of statistical analysis, predictive modeling, and data mining methodologies. 

Proven capability of deploying machine learning models into production at scale. 

Familiarity with CI/CD pipelines, containerization (Docker), and version control (Git). 

  
Preferred: 
Experience with Kubernetes orchestration systems. 

Familiarity with Snowflake data warehousing and NoSQL databases like MongoDB. 

Hands-on experience with messaging systems (e.g., Kafka). 

Exposure to distributed computing frameworks such as Hadoop, Spark, and Ray. 

  
Qualifications: 
Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related fields. A Ph.D. is advantageous. 

7+ years of proven hands-on experience building ML/AI platforms, especially involving AWS SageMaker and distributed computing frameworks. 

  
Person Specification: 
Proactive, self-driven innovator who thrives in fast-paced environments. 

Exceptional technical leadership skills combined with strong attention to detail. 

Outstanding communication skills, capable of clearly articulating technical concepts to diverse audiences. 

Ability to effectively bridge business and technical teams, ensuring alignment on objectives and outcomes. 

  
 



About us: Our story

Collinson Group is a global leader in driving loyalty and engagement for many of the world’s largest companies. Predominantly through the provision of travel related benefits within a market leading digital travel ecosystem. The group offers a unique blend of industry and sector specialists who together provide market-leading experience in delivering products and services across four core capabilities: Loyalty, Lifestyle Benefits and Insurance.

The group provides unrivalled insight and expertise around affluent consumers and frequent travellers, creating and delivering products and services now accessible to over 400m end consumers.

We have more than 25 years’ experience, with 28 global locations, servicing over 800 clients in 170 countries, employing 1,800 people.

We have been bringing innovation to the market since inception – from launching the first independent global VIP lounge access Programme, Priority Pass to being the first to sell direct travel insurance in the UK through Columbus Direct and creating the first loyalty agency of its kind in the travel sector with ICLP. Today we still invest heavily in innovation to ensure that we continue to deliver superior customer experiences.

Key clients include: Visa, Mastercard, American Express, Cathay Pacific, British Airways, LATAM, Flying Blue, Accor, EasyJet, HSBC, Chase, HDFC.

Our mission is focused on doing good beyond profit, which for us means we seek out opportunities for our people to share in our success and that we give back to the communities and people within which we work.

Never short of ambition, the success of our business is delivered through the diverse and talented team of over 1,800 colleagues globally.

Equal Opportunities: Our commitment to inclusion

Collinson is an equal opportunity employer and welcomes differences in all their forms including: colour, race, ethnicity, gender identity, sexual orientation, neurodivergence, family status, age, individuals with disabilities and people from all backgrounds, cultures and experiences as we strongly believe this contributes to our on-going success.

We are focused on continually evolving our purpose driven, high performing culture, providing an environment where our people have the opportunity to achieve their full potential and do interesting and meaningful work. Our company values are: Act smarter, Do the right thing, One team and Be insight led. These help guide everything we do internally in terms of how we think, act and interact, right through to how we deliver value to our customers and clients.

If you need any extra support throughout the interview process, then please email us at recruitment@collinson.com

Reward & Benefits: What's in it for me?

You can look forward to a competitive salary and benefit plan including but not limited to:

• Hybrid work arrangement (work from home/office)

• 26 calendar days Annual Leave

• Health Insurance

• Maternity leave (6 months- Paid)

• Paternity leave (15 days- Paid)