Senior MLOps Engineer

Quantexa
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Data Engineer

Senior Data Scientist

Lead Data/Head of Data Engineer

Senior Machine Learning Engineer - Research

Senior Data Analyst

What we’re all about. 

Do you ever have the urge to do things better than the last time? We do. And it’s this urge that drives us every day. Our environment of discovery and innovation means we’re able to create deep and valuable relationships with our clients to create real change for them and their industries. It’s what got us here – and it’s what will make our future. At Quantexa, you’ll experience autonomy and support in equal measures allowing you to form a career that matches your ambitions. 41% of our colleagues come from an ethnic or religious minority background. We speak over 20 languages across our 47 nationalities, creating a sense of belonging for all.

Founded in 2016 by a small team, Quantexa was built with a vision of enabling better decision making through better data-driven intelligence. Seven years, twelve locations and 700+ employees later we recently gained “Unicorn” status with our Series E funding round.  

Our Analytics teams build, deploy and maintain the a wide range of AI models which underpin our platform. This includes specific expertise in emerging methods for Graph based model and NLP models. Our MLOps team is task with automating and maximising efficiency of the build, deployment and maintenance of all model types.  

We are seeking a senior MLOps Engineer to join our team. This individual will play a crucial role in designing, deploying, and maintaining production-level machine learning models. The Senior MLOps Engineer will focus on leading MLOps initiatives, including infrastructure, automation, and ensuring models are seamlessly transitioned from development to production. 

The role demands technical expertise in MLOps, experience in collaborating with remote teams,  

Requirements

What do I need to have?

  • You’ll have a background in hands-on technical development, with significant industry experience in a data science/engineering role or similar
  • Good knowledge of the machine learning development cycle
  • Strong programming skills in Python and experience using ML libraries
  • Experience with Cloud technologies (we use GCP internally)
  • Experience with Docker, Helm and  Kubernetes for deploying and managing containerized applications
  • Experience with DevOps tooling like Airflow, Jenkins or similar

Experience in the following would be beneficial:

  • Experience deploying machine learning models into production, including managing their lifecycle
  • Experience implementing model governance e.g. model versioning, drift reporting etc.
  • Experience with MLOps tools such as MLFlow, Kubeflow, or DVC
  • Experience with distributed processing systems like Spark (Scala and PySpark would be invaluable)
  • Experience in programming with  Scala
  • Experience with LLMs, and/or RAG architecture
  • Experience optimizing model inference for GPUs and deploying models with specialized hardware requirements
  • Experience mentoring junior engineers within a team to help them grow

Benefits

We know that just having an excellent glass door rating isn’t enough, so we’ve put together a competitive package as a way of saying thank you for all your hard work and dedication.

We offer:

  • Competitive salary 💰
  • Company bonus
  • Private healthcare, Life Insurance & Income Protection
  • Cycle Scheme and TechScheme
  • Free Calm App Subscription #1 app for meditation, relaxation and sleep 🧘‍♀️
  • Pension Scheme with a company contribution of 6% (if you contribute 3%)
  • 25 days annual leave (with the option to buy up to 5 days) + birthday off! 🌴
  • Ongoing personal development
  • Great WeWork Office Space & Company wide socials

Our mission

We have one mission. To help businesses grow. To make data easier. And to make the world a better place. We’re not a start-up. Not anymore. But we’ve not been around that long either. What we are is a collection of bright, passionate minds harnessing complexities and helping our clients and their communities. One culture, made of many. Heading in one direction – the future.

It's all about you

Quantexa is proud to be an Equal Opportunity Employer. We’re dedicated to creating an inclusive and diverse work environment, where everyone feels welcome, valued, and respected. We want to hear from people who are passionate about their work and align with our values. Qualified applications will receive consideration for employment without regard to their race, colour, ancestry, religion, national origin, sex, sexual orientation, gender identity, age, citizenship, marital, disability, or veteran status. Whoever you are, if you’re a curious, caring, and authentic human being who wants to help push the boundaries of what’s possible, we want to hear from you.


Internal pay equity across departments is crucial to our global compensation philosophy. Grade level and salary ranges are determined through interviews and a review of experience, education, training, knowledge, skills, and abilities of the applicant, equity with other team members, and alignment with market data.

Quantexa is committed to providing reasonable accommodations in our talent acquisition processes. If you require support, please inform our Talent Acquisition Team.

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.