Machine Learning Engineer

Recruiter
DataSine
Location
Broadgate
Posted
12 Oct 2018
Closes
17 Oct 2018
Contract Type
Permanent
Hours
Full Time
Job description

DataSine (Techstars ‘16) is an award-winning venture-backed startup looking for a machine learning engineer to join its core research team.

We’re building a software platform that’s changing how companies personalise their services in the digital age, combining machine learning and applied psychology to help them effortlessly build effective and engaging customer experiences. We’re already helping financial institutions across Europe communicate and engage their customers better, and we’re looking to scale our SaaS technology to power marketing departments across multiple industries. Our machine learning challenges bridge everything from computer vision and computational aesthetics, to natural language generation and reinforcement learning.

You will be joining a small and vital team, and will be instrumental in crafting the process and culture of the department. As the ideal candidate you will have commercial experience as a software engineer, alongside strong and practical knowledge working with data and machine learning. We are looking for a self-starter who can quickly prototype, test and prove MVP machine learning systems, and communicate their results clearly to the team. DataSine has an international client base and there are opportunities for travel.

You’ll get to use those skills in a large variety of domains including:

Image classification
Natural language processing and generation
Reinforcement learning

Ideal candidates will have the following experience and technical skills:

Professional software engineering experience, working in teams together on a shared codebase
Great python ml stack knowledge (numpy, pandas, scikit-learn, pytorch, tensorflow)
Great practical machine learning experience (not necessarily professional) - the ability to talk about projects you have completed is a must, anything from great kaggle projects done in your spare time to fully implemented, production-ready machine learning pipelines
And any of the following will count positively to your application:

Postgraduate academic machine learning or related degree (e.g. computational statistics, data science)
Experience with data engineering best practices, big data technologies (spark, pig, hive) and data pipeline systems (airflow, luigi)
Foreign language skills

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