Do you want to make a real difference to real people's lives? Want to design and build fair and explainable systems which automate recruitment processes across Amazon? Come and be part of a team that develops new machine learning (ML) technologies, which help Amazon scale for its customers by recruiting diverse teams.
Key job responsibilities
You will work as an ML scientist in a team of other scientists and software developers. You will primarily be writing solutions in Python and will be using the latest technologies including AWS (e.g. Sagemaker). You will be contributing regularly to the code base as this is an applied role with the expectation of 50% of your time spent on the code. Your solutions will meet remarkably high standards of performance and reliability, and will operate at massive scale.
You will work as part of a sustainably paced agile team. You will play a hands on role in your team giving you the responsibility, authority, and autonomy to ensure success. You will be involved in every aspect of the process - from idea generation, customer engagement, business analysis and scientific design through to software development and operations.
We are looking for ML scientists who can delight our customers by continually learning and inventing and who want to use their expertise to solve real business problems. Our ideal candidate has a strong scientific foundation and experience of statistical analysis and model building and has a passion for fairness and explainability in ML systems.
The role offers an exceptional opportunity for growth and to make a real difference to Amazon recruitment. If you are selected, you have the opportunity to really impact our business by inventing, improving, and building world class systems, delivering results, working on exciting and challenging projects.
A day in the life
Amazon is looking for an Applied Scientist. As an scientist working at Amazon, you will play a key role in identifying business opportunities, measuring opportunity, inventing and prototyping solutions. You will use a wide range of technologies, programming languages and systems, and work alongside an experienced engineering team. You will have the freedom and encouragement to explore your own ideas and the reward of seeing your contributions benefit millions of customers worldwide.
About the team
Join a team full of talented people who come from all over the world. Enjoy the chance to work in a relaxed setting with a good social life. The team, primarily based in Edinburgh, Scotland, is rapidly expanding.
· Experience programming in Java, C++, Python or related language
· Experience of building machine learning models for business application
· PhD or equivalent Master's Degree plus experience in CS, CE, ML or related field
· Strong computer science grounding in a broad range of algorithms and data-structures.
· Proficiency with at least one mathematical programming environment (Numpy/Scipy, MXNet, PyTorch, TensorFlow, R, Matlab, SAS, etc.)
· Programming skills sufficient to extract, transform, and clean large data sets.
· Excellent critical thinking skills, combined with the ability to present your ideas clearly and compellingly in both verbal and written form.
· Strong written and verbal English communication skills.
· Ph.D. degree in Machine Learning, Data Science, Computer Science, or related field.
· Passion for fairness and explainability in machine learning systems.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
All offers are conditional on references, verification of the right to work in the UK, and successful background screening check. This will include previous employment verification, qualification verification (if relevant) and a relevant criminal check.