National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Machine Learning Engineer

Marley Health
London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer | Cambridge | Consulting

Machine Learning Engineer (SC Cleared)

Machine Learning Engineer

Machine Learning Engineer

Job Description
Location: London (Paddington) + travel to partner locations in Oxford and Cambridge areas

(Hybrid – 3 days/week in-office) .
Reports to: Chief Product Officer (CPO)
Start Date: July 2025
Employment Type: Full-time, Permanent

About Marley Health
Marley Health is redefining proactive pet care through clinically validated biomarkers, wearable technology, and data-powered diagnostics. Spun out of the University of Oxford and the Royal Veterinary College, we’re building a connected ecosystem for pet health that empowers veterinarians, insurers, and pet parents alike.

The Role - Purpose
We are looking for an experienced Machine Learning / Data Engineer to join the team - someone who is a collaborative doer and is eager to learn from and work with some of the leading minds in clinical machine learning and veterinary health data. This is a technical, delivery focused role that blends engineering responsibility with practical involvement in the essentials of getting data into product. You will need a good background in engineering practices for machine learning in the signal processing space. You’ll like working in a small team wearing multiple hats and creative problem solving.

What you’ll do – Key Responsibilities

:
Ensure that data is consumable by partners and third parties (including partner systems / apps integration.
Build and maintain data infrastructure, i.e., cloud-based pipelines using AWS, GCP, or Azure.
Build data pipelines and data infrastructure including working with modern ETL tools such as Dataflow, Airflow etc.
Help bridge product development team and data science lab.

What We’re Looking For

Qualifications and experience

Must haves:
Demonstrated (4-6 years minimum) industry experience.
Applied understanding of Machine Learning and Signal Processing working with time series analysis, data from sensors including irregular sample handling, filtering techniques, feature extraction from raw signals (e.g., accelerometery, ECG, temperature).
Previous hands on experience of packaging and deploying ML models to production environments or embedded systems.
Knowledge of working with embedded systems such as when inferences can be done on device, synchronisation cycles, power constraints, noise filtering etc.
Proficiency in Python, including libraries for data processing and machine learning.
Bash/Shell scripting for automation.
MSc in Computer Science or related field.
Nice to haves:
Familiarity with tools like Kafka, Apache Beam, or Spark (even at basic level) is a bonus.
Experience with Biomedical Data, such as working with biomedical sensors and a familiarity with clinical research practices.
Regulated industry experience (e.g., healthtech, medical devices) is a bonus, but not required.

What you’ll bring
A self-starter who is self-motivated, proactive, and thrives in an early-stage environment.
Not afraid to roll up your sleeves – you enjoy working directly with the tech and solving real-world problems for real users.
Ability to think strategically while straightening out the details.
Motivated by impact and excited to help build a truly novel product from the ground up.

Why Join Us

Build a product that sets a new clinical standard in pet health.
Work alongside a mission driven, no ego team focused on execution and excellence.
Make meaningful contributions every day – your work will directly shape our core product.
Join a fast-moving company backed by top-tier investors and world class scientific expertise.
Competitive salary + office space in London + 25 days holiday + company laptop & supporting tech + hybrid.

National AI Awards 2025

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.

Machine Learning Jobs Skills Radar 2026: Emerging Tools, Frameworks & Platforms to Learn Now

Machine learning is no longer confined to academic research—it's embedded in how UK companies detect fraud, recommend content, automate processes & forecast risk. But with model complexity rising and LLMs transforming workflows, employers are demanding new skills from machine learning professionals. Welcome to the Machine Learning Jobs Skills Radar 2026—your annual guide to the top languages, frameworks, platforms & tools shaping machine learning roles in the UK. Whether you're an aspiring ML engineer or a mid-career data scientist, this radar shows what to learn now to stay job-ready in 2026.

How to Find Hidden Machine Learning Jobs in the UK Using Professional Bodies like BCS, Turing Society & More

Machine learning (ML) continues to transform sectors across the UK—from fintech and retail to healthtech and autonomous systems. But while the demand for ML engineers, researchers, and applied scientists is growing, many of the best opportunities are never posted on traditional job boards. So, where do you find them? The answer lies in professional bodies, academic-industry networks, and tight-knit ML communities. In this guide, we’ll show you how to uncover hidden machine learning jobs in the UK by engaging with groups like the BCS (The Chartered Institute for IT), Turing Society, Alan Turing Institute, and others. We’ll explore how to use member directories, CPD events, SIGs (Special Interest Groups), and community projects to build connections, gain early access to job leads, and raise your professional profile in the ML ecosystem.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.