Senior Software Engineer

Unlikely
London
11 months ago
Applications closed

Related Jobs

View all jobs

On Senior Lead - Machine Learning Software Engineer

Senior MLOPs Engineer

Senior Machine Learning Engineer

Senior Simulation Engineer (Data Science)

Lead Software Engineer (Machine Learning)

Senior Machine Learning Engineer (Platform) - Bristol

At UnlikelyAI, we are building the future of AI: one that is reliable, accurate and transparent. Our Neurosymbolic technology harnesses the power of LLMs and generative AI, and combines it with Universal Language – our proprietary symbolic technology that bridges the gap between probabilistic machine learning and deterministic classical computing.

In order to make an application, simply read through the following job description and make sure to attach relevant documents.To meet the demands of our increasing commercial traction, we are looking for a smart, dedicated senior software engineer to join our world-class team. We are looking for someone who thrives on diving deep into code, to solve challenging and novel problems. You will have extensive software engineering experience, with exceptional coding ability ideally including experience in high-growth start-ups.This role will play a major role in developing our core capabilities, including working on how computers reason. You will work closely with other software engineers, research engineers and applied scientists in a heavily cross-functional environment.Required

Exceptional coding ability in at least one of our core languages: Java/Kotlin or Python.Previous experience working with complex algorithms and data structures.Experience in building well-tested code for production and a demonstrable history of advocating for software quality and evangelising best practices.Experience with leading the process from ideation to production for brand new software systems.Relevant degree: Computer Science, Mathematics, Engineering, STEM.Bias for action—able to move quickly and make informed decisions.Experience working with cloud computing (AWS preferred, but any provider is fine).Why Join Us?

Team

- We have a world-class team of intelligent, focused, collaborative people. We're ambitious, move fast and have a lot of fun while doing it.Vision

- We have a huge vision for the future. This offers a unique opportunity to work on the foundational layers of AI but, unlike many other companies, we're not just scaling LLMs, we're focused on a novel neuro-symbolic approach.Tech

- You'll work with our novel and cutting-edge tech. Driving this forward involves solving some exciting challenges, so our team has the freedom to be creative and explore innovative ideas in an environment where our technology is evolving and maturing.Location: We are currently operating a hybrid scheme with a small office near Holborn tube station available to anyone who wants to work there. We also have occasional team days where everyone meets face to face and days where people work heads down from home, communicating with colleagues using Slack and Zoom.Equal Opportunities: We are committed to having a truly diverse team where everyone is encouraged to be their authentic selves. We, therefore, do not discriminate in employment based on gender, race, religion, sexual orientation, national origin, political affiliation, disability, age, marital status, medical history, parental status or genetic information. Having a broad mix of people helps us to be the best we can.

#J-18808-Ljbffr

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 Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.