Deep Learning jobs and careers

Deep Learning is a subset of Deep Learning focused on artificial neural networks built on algorithms inspired by the function and structure of the brain. There is a large range of industries that utilize Machine Learning such as; Financial Services, Healthcare, Government, Marketing and Sales, Oil and Gas and Transport.

• Algorithm Researcher
• Computer Vision Engineer
• Computer Vision Expert
• Computer Vision Scientist
• Computer Vision Software Engineer
• Graduate Deep Learning Engineer
• Deep Learning Analyst
• Deep Learning Developer
• Deep Learning Engineer
• Deep Learning Researcher
• Deep Learning Specialist
• NLP & Deep Learning Scientist
• NLP Software Engineer
• Research Scientist – Deep Learning
• Research Scientist – Image Analysis
• Senior Computer Vision Researcher

Graduate Deep Learning Researcher
Deep Learning Engineer

We’ve outlined the latest salary benchmarks for Deep Learning roles in the guides below:

Data, Insight and Analytics Salary Guide

Data, Insight and Analytics Day Rate Guide

Data, Insight and Analytics Within Data Engineering Development Salary Guide

Data, Insight and Analytics Within Data Science Salary Guide

The skills needed can be split into 3 categories; fundamental skills, programming skills and machine learning languages.

Fundamental skills: Probability – using techniques like Markov Decision Processes and Bayes Nets | Statistics – being able to analyse variance and test hypotheses | Data Modelling – understanding the structure of datasets, spotting gaps and filling them with data.

Programming skills: Fundamentals – Data structures | Algorithms | Computer Architecture | b-trees | Sort Algos and Stacks | Software Design – A background in APIs e.g. web APIs and static/dynamic libraries | ML Libraries – e.g. TensorFlow, CNTK, MLib.

Machine Learning languages: C/C++ – e;g; LibSVM, Shark and mlpack | R | Python – NumPy, SciPy Pandas, scikit-learn, Theano, and TensorFlow.

Deep Learning skills: Supervised Learning | Unsupervised Learning | Input Layer | Hidden Layers | Output layer |  Neural Networks | Convolutional Neural Networks (CNN) | Recurrent Neural Networks (RNN) | Long/Short Term Memory (LSTM) | Markov Chain (MC) | Deep Convolutional Network (DCN).

There is a huge range of courses online that all you to improve your skills in these areas such as; Coursera, Udacity, and Kaggle.

A Masters (MSc) or Doctorate (PhD) in a maths, physics, statistics, artificial intelligence (AI), software engineering, engineering or computer science field with technical skills in programming. Statistics and probability are key here, as well as demonstrable experience working with large data sets and experience using machine learning and statistical methods.