Machine Learning Engineer

Job type: Permanent
Contact name: Eddie Woodley

Contact email: eddie@ds-group.co.uk
Job ref: 32333
Published: 21 days ago
Startdate: 13/06/2022

 

About the company:

DS Group have partnered with an exciting clean energy start-up based in Austin, Texas. This company bring together exceptionally talented and passionate people in the domains of energy trading, data science, software engineering and an in-depth understanding of flexible energy assets. Their aim is to maximise the value of large-scale flexible energy assets (eg, battery storage) so they are attractive investments, are deployed at scale and enable the energy transition. They are looking for smart, motivated people to join their team who share their belief that they can outperform the energy sector dinosaurs, have a positive impact on the planet and have fun doing it together.

They have a vacancy for a Machine Learning Engineer to join their team.

 

Responsibilities include:

  • Deploying their ML models in production environments
  • Interfacing with the Data Science team to help make their models production-ready at both the design and development stages
  • Support development and maintenance of their data architecture
  • Build internal tools for simple interaction with our data and models
  • Build and maintain real-time data streaming from numerous sources

 

They’re looking for someone who is a great fit for their company. They want people who take accountability, build trust and are innovative. They value diversity and their environment is supportive, challenging and focused on the consistent delivery of high quality, meaningful work. This is a hybrid role, going into the office at least 1 day per week.

 

Requirements:

  • Python - 3+ years of experience with (at least) the following packages, pandas, numpy, scipy and sqlalchemy
  • Strong AWS skills in an 24/7 operational environment in the context of ML models
  • Expert in SQL(postgres) and experience in designing efficient data models
  • Ability to help containerize ML services using docker, which are ready for live deploy and robust and scalable
  • You have experience with development, test and production environments, and knowledge and experience of using CI and CD.