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

Nominate & Attend

Engineering Manager

Annapurna
Liverpool
5 months ago
Applications closed

Related Jobs

View all jobs

Engineering Manager Data MLOps

Engineering Manager Data MLOps

Software Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Engineering Manager


Job Type:Permanent Position


Location:Hybrid (UK Based)


Start Date:ASAP



About The Company:


We are a leading developer of embodied intelligence for autonomous vehicles. We use AI to pioneer a next-generation approach to self-driving: AV2.0, which enables fleet operators to unlock the benefits of AV technology at scale. We were the first to deploy AVs on public roads with end-to-end deep learning.



The role:


  • Lead a multidisciplinary team of Software Engineers and Systems Engineers, setting clear objectives and milestones. Drive strategic software deployment across AV systems, aligning with the company’s objectives.
  • Oversee the design and implementation of software that supports full sensor integration and data capture, ensuring high quality and scalability necessary for autonomous operations.
  • Ensure the delivery and maintenance of soft-real-time applications on Linux-based platforms, focusing on data collection, storage, and on-edge machine learning inference.
  • Develop fault-tolerant software solutions with comprehensive diagnostic tools to swiftly address and resolve issues impacting the operational capacity of our deployed AV fleet.
  • Craft and utilize advanced system monitoring tools to enhance performance metrics and troubleshoot both ad-hoc and systemic issues effectively.
  • Efficiently allocate resources, including personnel and technical infrastructure, to meet project timelines and performance goals.


About you:


Essential

  • At least 2 years in a leadership role within software development or embedded systems, including directly managing a software development team through all stages of the software lifecycle.
  • Strong knowledge of software development for embedded systems, real-time data processing, and system diagnostics, preferably within the automotive or similar regulated industries.
  • Hands-on experience with Linux-based development, real-time systems, and edge computing. Proficiency in programming languages such as C++ or Rust, and experience with relevant software development tools and environments.


Desirable

  • Automotive Software:Background in developing automotive software, with knowledge of ASPICE, DriveOS, or AutoSAR
  • Educational Background:A Master’s degree or greater in Computer Science, Electrical Engineering, or a related field is desired



If you would like to have a chat about this exciting opportunity, apply below or reach out directly to

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.

Careers

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Jobs

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Careers Jobs

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

🍪 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.