Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

MLOps Engineer

IO Associates Careers
London
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Lead Data Scientist – NLP

Lead Data Scientist - NLP

Senior Data Engineer

Data Engineer (ML/AI Focus) - Healthcare Analytics  London | Hybrid

Data Engineer


MLOps Engineer

£500 - £550pd

Outside IR35

Remote

6 month contract

IO Associates have a contract position for an experienced Machine Learning Engineer to join an expanding startup

Founded over 8 years ago, they're creating groundbreaking solutions, utilising AI-driven digital nose technology capable of detecting an extensive range of scents. This innovative technology holds the potential to transform various sectors, and after substantial funding they are looking to expand

They are looking for an MLOps Engineer to transition their ML models from R&D into production. As an MLOps Engineer, you will build data pipeline monitoring and create solutions for effectively monitoring outputs of various types of regression, classification, neural network, and clustering.

Requirements;

  • Bachelor's degree or equivalent in data science, machine learning, computer science, mathematics, or statistics.
  • 3+ years of industry experience successfully implementing monitoring systems for ML models
  • Experience implementing validation and monitoring protocols for machine learning models
  • Fluent in Python.
  • Experience with TimescaleDB and AWS is a plus
  • Understanding of machine learning approaches and model training processes

Interested in hearing more? Please get in touch with Rebecca Long on ...

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.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Jobs

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.