Engineering Manager Data MLOps

Client Server; London; Hybrid; GBP 80,000 - 110,000; Full time

Job summary

Client Server is seeking an Engineering Manager specializing in Data MLOps and AI Machine Learning. Join a fast-growing startup at the forefront of hotel revenue optimization solutions. This role combines team leadership with hands-on technical responsibilities, focusing on scalability and performance of AI-driven services. A strong background in cloud computing and DevOps practices is essential for driving the success of critical platform components.

Benefits

Salary up to £110k + bonus

Pension

Training and career progression

Qualifications

• Strong technical background in cloud computing and modern DevOps practices.
• Experience with Machine Learning infrastructure and leading engineering teams.
• Ability to mentor engineers and own complex technical projects.

Responsibilities

• Lead the Science Platform team in building and maintaining the PaaS for AI solutions.
• Drive architectural decisions while remaining hands-on.
• Partner with Product Manager to define technical strategy and product roadmap.

Skills

Leadership

Cloud Computing

Distributed Systems

DevOps Practices

Machine Learning Infrastructure

Education

Degree in Computer Science or related field

Job description

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This range is provided by Client Server. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from Client Server

Engineering Manager (Data MLOps AI Machine Learning) London / Remote to £110k

Are you a data savvy hands-on technology leader?

You could be joining a well-funded and growing hotel revenue optimisation technology start-up that uses AI and complex algorithms to enable hotels to price their rooms according to demand; this is a £7 billion a year industry and the product is in great demand.

As an Engineering Manager you will lead a small, experienced, Science Platform team that are building and maintaining the Platform as a Service (PaaS) that enables development and operation of AI- first revenue optimisation solutions. You'll remain hands-on 80-90% of the time, driving architectural decisions and ensuring the platform's scalability, reliability and performance. You will input into longer term strategy, partnering with the Product Manager to define and execute technical strategy and the product roadmap and take ownership for the success of critical platform components including data science workflows, cloud environments, observability systems and Ci/CD infrastructure.

Location / WFH:

You can work from home most of the time, but must be commutable to London (within 3-4 hours) as you'll be expected to meet up with the team there around once a quarter.

About you:

• You have a strong technical background with cloud computing, distributed systems, and modern DevOps practices
• You have experience with Machine Learning infrastructure and Data Science workflows
• You have strong leadership skills and a proven ability to mentor engineers and foster a culture of technical excellence
• You have experience of taking ownership of complex technical initiatives and can drive them to completion
• You have excellent communication skills

What's in it for you:

• Salary to £110k + bonus
• Pension
• Training and career progression

Apply now to find out more about this Engineering Manager (Data MLOps AI Machine Learning) opportunity.

At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We're an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Software Development and Technology, Information and Media

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