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

Apply Now

Senior/Staff Machine Learning Engineer

HUG
London
5 months ago
Applications closed

Related Jobs

View all jobs

Staff Machine Learning Engineer

Staff Machine Learning Engineer

Staff Machine Learning Engineer

Staff Machine Learning Engineer

Senior Staff Machine Learning Scientist, Operations

Staff Machine Learning Engineer

Senior Machine Learning Engineer


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.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.