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Artificial Intelligence Engineer

Who you’ll be working with

Do you want to make a real difference in your career, a difference that affects people’s lives and transforms the way companies and government operate? Do you want to amaze people, to take them on a journey and show them something truly fantastic?  Do you want to be at the forefront of the AI revolution?

This is what we are doing at Capgemini.

The Smart Analytics practice is part of Capgemini’s global Insights & Data group; our goal is to help the organisations we work with become truly ‘insight driven’, to fully exploit their data using the convergence of Cloud and Artificial Intelligence to deliver real business value.  We marry the most innovative insights solutions with rock solid, industrialised engineering.

The focus of your role

If we believed all the stories about AI, then we’D be looking for budding magicians, wizards and sorcerers; but we don’t.  So, whilst the reality is still, quite frankly, amazing, that’s achieved through a lot of ‘smarts’, rather than magic fairy dust.  We want passionate, energetic people who live and breathe all things AI, whether that be machine learning, deep learning, computer vision and so on, combined with great software engineering skills…no point creating great models if we can’t deploy them!  We want you to be thinking “how can I use what I know?”, “what do I need to learn?” in order to help your client achieve their business goals. 

We take career progression seriously; many of the Insights & Data UK management and the Smart Analytics practice leads did not join in senior positions, rather they were given the opportunities from within to progress.  We really do try to balance the needs of the business with the needs and aspirations of the individual…it is in our interests for our people to be happy and successful.

What you’ll do

We don’t really have a typical day or typical project at Capgemini.  Our clients expect advise, proof-of-values, industrialised solutions; we work on small and very large engagements and we work across several different sectors, including public, CPG, retail, manufacturing and utilities.  If you aren’t on a project, you could instead be involved in a bid, doing some training, working on a point-of-view, building a demo or contributing to our blog series (tips from recent new joiners, who we are happy for you to speak with, is just ‘get stuck in’).  In recent months, we’ve done some pretty cool stuff, like used Tensor Flow in a model looking at acoustics of voice recordings, used ESA radar data to classify UK vegetation and massive scale Spark for image processing at an O&G client.  

What you’ll bring

We are looking to bring in people at all levels, so whilst the list of skills below is fairly heavy, please do get in touch even if you only have two or three.

Detailed knowledge on a range of AI techniques (e.g. supervised and un-supervised machine learning techniques, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.)

Experience using Python, R or Spark to extract insights from data

Knowledge of SQL for accessing and processing data (PostgreSQL preferred but general SQL knowledge more important)

Experience using the latest Data Science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g. Tensorflow, MXNet, scikit-learn)

Software engineering practices (coding practices to DS, unit testing, version control, code review)

Hadoop (especially the Cloudera and Hortonworks distributions), other NoSQL (especially Neo4j and Elastic), and streaming technologies (especially Spark Streaming)

Alchemy, spell casting and potion making

Deep understanding of data manipulation/wrangling techniques

Experience using development and deployment technologies, for instance virtualisation and management (e.g. Vagrant, Virtualbox), continuous integration tools (e.g. Jenkins, Concourse, Drone, Bamboo), configuration management tooling (e.g. Ansible) and containerisation technologies (e.g. Docker, Kubernetes, Swarm)

Delivering insights using visualisation tools or libraries (Javascript preferred)

Experience building and deploying solutions to Cloud (AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. Terraform)

Strong interpersonal skills with the ability to work with clients to establish requirements in non-technical language.

Ability to translate business requirements into plausible technical solutions for articulation to other development staff.

Experience designing Data Science deliveries, planning projects and/or leading teams

We have a great team @ Smart Analytics and would love to hear from you.  If you want to chat informally before applying, that’s fine too.  Just reach out to any of us below on LinkedIn

Lee Brown

Toby Balfre

Antonio Sawaya

Toby Gamm


What we’ll offer you

Professional development. Accelerated career progression. An environment that encourages entrepreneurial spirit. It’s all on offer at Capgemini. And although collaboration is at the core of the way we work, we also recognise individual needs with a flexible benefits package you can tailor to suit you.

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