Machine Learning Engineer

Job description

EY Global Delivery Services means 40.000 specialists providing globally IT, project management and strategic business services to EY member firms. In addition we deliver support and solutions to clients from all over the world.

EY is a global leader in assurance, tax, transaction and advisory services. Technology is at the heart of what we do and deliver at EY. Technology solutions are integrated in the client services we deliver and are key to our innovation as an organization.  

Fueled by strategic investment in technology and innovation, Client Technology seeks to drive growth opportunities and solve complex business problems for our clients through building a robust platform for business and powerful product engine that are vital to innovation at scale. As part of Client Technology, you’ll work with technologists and business experts, blending EY’s deep industry knowledge and innovative ideas with our platforms, capabilities, and technical expertise. As a catalyst for change and growth, you’ll be at the forefront of integrating emerging technologies from AI to Data Analytics into every corner of what we do at EY. That means more growth for you, exciting learning opportunities, career choices, and the chance to make a real impact.

The opportunity

The selected candidate: 

·  Develops and reviews complex data analytics models, algorithms, systems and solutions, using advanced and specialist data science, programming and analytical techniques
·  Delivers complex predictive models and identifies new projects, opportunities and data sources which can be used to drive measurable client and commercial benefit
·  Provides insights and recommendations from different data sources to senior team members to help make decisions that drive better business outcomes for clients

Your key responsibility

·  Design and implement scalable ML and DL systems, products, and solutions.
·  Collaborate with engineering and DevOps teams to build and deliver systems that can be deployed both in the cloud and on premise, e.g., using Azure, Docker, and Kubernetes.
·  Build deep learning-based products on CPUs and GPUs, leveraging latest deep learning and machine learning libraries.

Skills and attributes for success

·  Machine Learning skill : Capability to develop and use algorithms that analyze a data set, which then self-learn from that Analysis to improve the predictions made by these algorithms. The more often the algorithm is run / optimized, the more it learns and improves.  This can then be used to make data-driven predictions.​​
·  Third Party AI Tools : Google API, Amazon Web Services Machine Learning API, Google TensorFlow, Theano, Caffe, Kera, CNTK, Microsoft Distributed Machine Learning Toolkit

To qualify for the role, you must have

·  Bachelor's Degree in Actuarial, Behaviour Economics, Computer Science, Data Analytics, Data Science, Econometrics, Engineering, IT, Cyber Security, or related field preferred 
·  Strong mathematics and algorithms background/skills
·  Strong software engineering skills
·  Experience working as a back end engineer in Java / Python / C / C++ or C# or equivalent
·  Some experience with modern software development including Cloud, DevOps, NoSql, and CI/CD.
·  Understand the fundamentals of deep learning, and machine learning, e.g., over-fitting, IID data.
·  Good understanding of standard machine learning and deep learning techniques

Ideally, you’ll also have

·  Experience building AI systems using one of TensorFlow, PyTorch, MXNet, Theano, Caffe, and other open source frameworks. Solid understanding of underlying techniques in deep learning to build for scalability, and efficiency.
·  Experience building machine learning products.
·  Experience building scalable machine learning and deep learning systems.

What we look for

·  A self-starter, independent-thinker, curious and creative person with ambition and passion

If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.

Make your mark.

Apply now.