Algorithm Product Lead

Defence
Liverpool
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Senior Data Scientist

Data Scientist - Featurespace

Data Scientist - Fixed-Term Contract

Data Scientist-Senior Manager

Applied Machine Learning Lead

This dynamic role offers the chance to make a tangible impact, working with technologies like MATLAB, Simulink, and Python. With brilliant ability for career progression, this is an exciting opportunity for someone passionate about leadership and technical excellence.

This hybrid role typically requires 3-4 days per week on-site due to workload classification. Candidates must be British citizens or dual UK nationals with British citizenship and pass security clearance.

Key Responsibilities:

  • Lead and develop a high-performing team
  • Drive algorithm design to meet system requirements
  • Collaborate with engineering and software teams for implementation
  • Ensure robust and reliable algorithm development
  • Represent the team to senior leadership and external partners

Essential Criteria:

  • Experience leading technical teams and projects
  • Strong communication and prioritisation skills
  • Ability to motivate and focus a team on objectives

Desirable Experience:

  • Software development, data science, mathematical modelling, and tools like MATLAB, Simulink, Python


Benefits:

  • Annual bonus potential.
  • 25 days of annual leave, with the option to purchase more.
  • Flexible working arrangements and support for ongoing learning.
  • Comprehensive health and dental insurance options, among others.
  • Enhanced Parental Leave: offers up to 26 weeks for maternity, adoption and shared parental leave. Enhancements are available for paternity leave, neonatal leave and fertility testing and treatments.
  • Facilities: Including subsidised meals.

Even If you feel like you don't meet every qualification, we encourage you to reach out an apply.


JBRP1_UKTJ

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.

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

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

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

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.