At a Glance
- Tasks: Lead a team to deliver scalable ML systems and mentor engineers.
- Company: Major, well-established organisation in West London with a hybrid work model.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic role with a focus on collaboration and engineering excellence.
- Why this job: Combine technical expertise with leadership to drive innovative ML projects.
- Qualifications: 10+ years in Software or ML Engineering, strong Python skills, and team management experience.
The predicted salary is between 75600 - 92400 £ per year.
We're recruiting on behalf of a major, well-established organisation for an MLOps Technical Manager to lead a growing ML engineering function. This is a genuinely interesting project: you'll work closely with data scientists, maintenance engineers, and cross-functional stakeholders to deliver scalable ML systems — including predictive maintenance, fault detection, and component lifecycle optimisation.
You'll own end-to-end technical delivery of ML systems, from backend infrastructure through to frontend integration, while leading and mentoring a team of engineers. This is a hands-on leadership (40% hands on) role for someone who wants to combine deep technical ownership with people management and senior stakeholder engagement.
Key Responsibilities
- Technical Leadership
- Own the end-to-end technical delivery of ML systems, from backend infrastructure to frontend integration
- Lead architectural decisions across the ML stack, ensuring scalability, reliability, and alignment with business goals
- Drive the ongoing migration from MLflow to AWS SageMaker, maintaining continuity and minimising disruption
- Define and enforce MLOps best practices across model training, serving, monitoring, and deployment
- MLOps & Engineering
- Design and maintain scalable ML infrastructure supporting batch and real-time environments
- Oversee the implementation of robust ETL/ELT pipelines, feature engineering, and data processing at scale
- Ensure model training, serving, and monitoring pipelines are production-grade and optimised for performance
- Develop and maintain React-based frontend interfaces that surface ML insights to operational and engineering stakeholders
- Champion CI/CD practices and contribute to a culture of engineering excellence
- Team & Stakeholder Management
- Lead, mentor, and provide structured feedback to a team of engineers, fostering a high-performance culture
- Collaborate closely with cross-functional stakeholders across engineering, data science, and operations
- Communicate complex technical decisions clearly to both technical and non-technical audiences
- Identify and address technical blockers proactively, keeping delivery momentum and team
Qualifications
- Must-Have
- 10+ years of experience in Software, Data, or ML Engineering roles
- Proven track record as a Tech Lead (managing teams of 5+ people), owning end-to-end technical delivery across backend and frontend systems
- Deep expertise in MLOps, including model training pipelines, serving infrastructure, monitoring, and CI/CD
- Expert-level proficiency in Python — this is non-negotiable
- Strong hands-on experience with MLflow (mandatory)
- Solid experience with AWS and cloud-native architectures
- Frontend proficiency in React, with the ability to deliver end-to-end product features
- Hands-on experience with ETL/ELT pipelines, data engineering, and large-scale data processing
- Experience with containerisation (Docker) and scalable data systems (e.g. Spark, Kafka)
- Nice-to-Have
- Experience with AWS SageMaker or similar managed ML platforms
- Background in safety-critical or regulated industries (aerospace, aviation, or similar)
- Familiarity with Kafka or event-driven architectures for real-time ML pipelines
Soft Skills
- Strong leadership presence with the ability to give and receive structured, constructive feedback
- Excellent communicator across technical and business stakeholders — comfortable navigating complex organisational dynamics
- Strategic thinker with a hands-on execution mindset
- Proactive and collaborative, with the confidence to ask questions, challenge assumptions, and share ideas openly
- Empathetic team leader who drives accountability and high performance without micromanaging
Interested? Get in touch to find out more and have a confidential conversation about the role.
MLOps manager in Slough employer: Uniting Ambition
Uniting Ambition is an excellent employer that fosters a collaborative and innovative work culture, providing employees with the opportunity to engage in meaningful projects that drive modernisation in database management. With flexible remote and hybrid working options, along with a strong focus on professional development, team members can thrive in their roles while enjoying a healthy work-life balance. The supportive environment encourages growth and offers unique advantages for those looking to make a significant impact in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps manager in Slough
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Uniting Ambition or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
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We think you need these skills to ace MLOps manager in Slough
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Uniting Ambition.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Uniting Ambition and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Uniting Ambition
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Uniting Ambition uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
