Senior/Staff Machine Learning Engineer

HUG
London
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Staff Engineer (Machine Learning) – 45391

Staff Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Scientist

Machine Learning Engineer (Manager)

Machine Learning Engineer (Manager)

Senior Machine Learning Engineer



Skills, Experience, Qualifications, If you have the right match for this opportunity, then make sure to apply today.

About the Role

Are you ready to redefine how logistics operates in a rapidly evolving world? HUG is proud to be collaborating with an innovative start up that’s revolutionising delivery through smarter, more sustainable solutions. Their mission is to create systems that benefit communities, reduce environmental impact, and enhance the customer experience.


This is your chance to join a rapidly growing team at the forefront of logistics innovation, creating impactful technology that’s reshaping how goods move in the modern world. With recent funding secured and ambitious growth plans underway, there’s never been a more exciting time to come on board.


Responsibilities

  • Develop and deploy ML models for various logistics applications.
  • Engineer features and set up ML infrastructure.
  • Collaborate with wider technology and operations teams.
  • Spend time in the field to understand technology impact.


Requirements

  • 2+ years experience deploying ML models in production.
  • 4+ years software engineering experience.
  • Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch).
  • Experience with cloud platforms, preferably Google Cloud.
  • Strong communication and collaboration skills.


Benefits

  • Competitive salary and equity package.
  • Comprehensive health insurance.
  • Flexible hybrid working from a dog-friendly London office.
  • Free gym membership.
  • Cycle-to-work scheme.
  • Culture of learning and growth.
  • Team social events.

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 for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.