Machine Learning Engineer
Posted on Nov 7, 2020 by Gazelle Global Consulting
As a Senior ML Engineer for my client, you will take on complex data problems surrounding personalisation, search, recommendations, audience segmentation, forecasting, and reporting.
You will build data-driven solutions to bring excellent user experiences to their user base.
You will work with some of the most diverse datasets available - user behaviours, acoustical analysis, revenue streams, cultural and contextual data, and other signals across our broad range of mobile and connected platforms.
Above all, your work will impact the way the world experiences music and the way creators connect to their fans.
What you'll do:
- Contribute to designing, building, evaluating, shipping, and improving the client's products by the means of hands-on ML development.
- Collaborate with a cross-functional agile team spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and relevant ways.
- Prototype new approaches and productionise solutions at scale for the client's users.
- Help drive optimisation, testing, and tooling to improve quality.
- Be part of an active group of machine learning practitioners across the business.
Who you are:
- You have a strong background in data science and machine learning, with experience and expertise in designing, building, and testing models.
- You have 5+ years of hands-on experience implementing production machine learning systems at scale in Python, Scala, Java, or similar languages. Experience with frameworks such as Scikit-learn and Spark-ML is desired. Experience with Tensorflow and Pytorch is a plus.
- You preferably have experience with data pipeline tools like Apache Beam or even our open-source API for it, Scio and cloud platforms like GCP or AWS. Expertise with relational databases (Postgres, MySQL) is desirable. Experience with BigQuery is a plus.
- You care about agile software processes, data-driven development, reliability, and responsible experimentation.
- You understand the value of collaboration within teams
Please send me your CV for immediate consideration.