AI Engineer

Inference Group
Manchester
11 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist - Contract

Data Scientist / AI Engineer

Data Scientist (Government)

Data Engineer (AI Analytics and EdTech Developments)

Data Engineer (AI Analytics and EdTech Developments)

Junior AI Data Engineer

Who are Inference Group?


Are you excited by being a part of a company that’s redefining the future of data and AI? Welcome to Inference Group, where we’re not just a tech startup – we’re a team of passionate innovators devoted to empowering businesses through the transformative power of data, machine learning, and AI.


At Inference Group, we’re on a mission to help businesses unlock their true potential and drive sustainable growth. As we rapidly expand, we’re looking for like-minded, creative technical experts who want to make a real impact. Here, you’ll work alongside leading experts in data, AI, and technology - helping to guide our customers in harnessing the full potential of their data.


Join us, and you’ll be at the forefront of the data and AI revolution. You’ll have the opportunity to turn cutting-edge concepts into scalable, operational solutions that enhance human creativity and decision-making. Our team is committed to delivering innovative investigative solutions to customers worldwide, helping them navigate and thrive in an AI-driven world.


As we continue to grow we are now seeking a skilled AI Engineer to broaden our engineering capabilities - this will involve creating, programming and training complex networks of algorithms to grow our AI programmes, evaluating and comparing algorithm performance based on large, real-world data sets, designing and implementing Machine Learning algorithms and undertaking various data mining exercises from various sources to gain valuable insights to accelerate existing algorithms and future models.


This role will involve oversight of ongoing AI/ML engineering projects where you will play a crucial role in supporting our clients objectives by providing important technical insights into ongoing tech transformation and delivery, this will involve creating intelligent AI models which utilise deep learning, neural networks and ML algorithms to gain key business insights and create opportunities for informed decision making and future planning.


We are looking for someone well versed in programming, software engineering and data science fields with solid previous experience of building, training and deployment using Microsoft Azure products who is passionate and curious about ongoing development within the AI/ML space and dedicated to creating new opportunities for our clients to learn and evolve within these fields.


The ideal person for this role would have previous experience of delivering engineering projects focused on realising the potential of AI/ML within a similar consultancy space with hands on experience of using all or some of the following technologies; Azure Machine Learning (Azure ML), Azure Kubernetes Service (AKS), Azure Data Lake Storage, Azure Cosmos DB, Azure SQL Database, Azure DevOps, PowerBI, Azure OpenAI Service ect


This role provides a unique opportunity for a proactive and driven person to take their engineering career to the next level. We are excited to work with someone who considers themselves a Tech Enthusiast - you love tech and can’t wait to learn more about projects, systems and data, with an aptitude for challenging existing ways of working, able recognise opportunities and identify innovative solutions that add real value to clients.


If you’re a driven person with a love of life long learning, who is naturally curious and eager to contribute to the early stages of a dynamic consultancy, we would love to have you on board! As a team, we will explore the limitless opportunities of data and AI, driving excellence and having a lot of fun along the way.


We are a young, small company experiencing exciting growth and we are devoted to hire people at this stage who will be future leaders within our business. We are committed to your ongoing learning and development and love working with curious, life long learners - we have access to the latest technology and will provide training in these and certifications to help you grow and succeed.


As AI is constantly changing and evolving, we make a promise to our customers that we foster a culture of excellent people who have the most up to date training, knowledge and experience to help deliver innovative solutions.


If you like our mission and connect with our values, we encourage you to apply.

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 Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

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

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

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

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.