Machine Learning Scientist

Job description

DESCRIPTION

As part of Amazon's AWS AI Labs Berlin you will focus on Machine Learning methods and systems for time series analysis and related areas. The team covers many of Amazon's diverse time series use-cases such as anomaly detection and forecasting. These problems come in challenging problem complexity and scale. The team works in the intersection between probabilistic machine learning and deep learning.

The team develops novel, production-ready methods which means that an applied scientist in the team is required to have both deep theoretic understanding of Machine Learning with a proven track record of scientific publications in ML or a comparable field as well as strong coding skills in a non-prototyping language.

Major responsibilities:
- Research, design, implement and evaluate novel time series models and algorithms in our own forecasting toolbox which meets Amazon's production requirements
- Work on large-scale datasets, focusing on creating scalable and accurate time series systems in versatile application fields
- Collaborate closely with research team members on developing systems from prototyping to production level
- Collaborate with teams spread all over the world
- Track general business activity and provide clear, compelling management reports on a regular basis

PREFERRED QUALIFICATIONS

If you thrive in a challenging and fast-paced environment, you’ll meet your match with us, as you will be part of a vibe of constant improvement. We don’t like to sit still, which is why we always treat every day like the first day. A day to make more good things happen for our customers. It’s that kind of spirit that drives our success now and keeps us ahead of the competition in the future. And you could be part of it. It’s as simple as this: Work Hard. Have Fun. Make History.
Sounds interesting?

Desired profile

BASIC QUALIFICATIONS

Required Qualifications:
- Research experience in machine learning, machine learning systems and ideally in time series proven by scientific track record
- Deep understanding of machine learning fundamentals
- Strong coding skills in two or more programming languages where one is Java, Scala, C/C++ or similar and the other is Python, Julia or similar.
- Strong verbal and written communication skills
- Excellent problem solving ability