Machine Learning Operations (MLOps) Engineer
Flexible Location – Ipswich, London or Selby
Permanent, full time
We generate dispatchable, renewable power and create stable energy in an uncertain world. Building on our proud heritage, we have ambition to become the global leader in sustainable biomass and carbon removals.
We’re enabling a zero carbon, lower cost energy future for all, and working hard to decarbonise the planet for generations to come.
As a Machine Learning Operations (MLOps) Engineer, you’ll be responsible for managing, releasing and monitoring Machine Learning (ML) and Artificial Intelligence (AI) artefacts using automated frameworks. You’ll also optimise ML/AI code written by our Data Scientists into Production-ready software according to agreed performance and cost criteria.
You’ll play a key role ensuring that ML/AI projects are setup for success via the automation of residual manual steps in the development and production lifecycle. You’ll also provide essential insights into the ongoing predictive capability and cost of deployed ML/AI assets using language and visualisations appropriate for your audience.
It’s an opportunity to work across multiple projects concurrently. You’ll use your judgement to determine which projects and teams need most of your time. You’ll use your cross-project exposure to feedback to the Data & Data Science Leadership Team to guide understanding, improve consistency, and develop & implement initiatives to improve the community for the future.
You’ll need strong experience delivering and monitoring and scalable ML/AI solutions via automated ML Ops.
Expert knowledge of Python and SQL, inc. Numpy, Pandas, PySpark and Spark SQL
- Expert knowledge of ML Ops frameworks in the following categories:
b) orchestration of ML workflows (e.g. c) data and pipeline versioning (e.g. Data Version Control)
d) model deployment, serving and monitoring (e.g. Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform
- Working knowledge of one or more ML engineering frameworks (e.g. Working knowledge of object-oriented programming and unit testing in Python
- Working knowledge of application and information security principles and practices (e.g. OWASP for Machine Learning)
- Working knowledge of Unix-based CLI commands, source control and scripting
- Working knowledge of a cloud data platform (e.g. Databricks) and a data lakehouse architecture (e.g. Working knowledge of the AWS cloud technology stack (i.e. As you help us to shape the future, we’ve shaped our rewards and benefits to help you thrive and support your lifestyle:
- Competitive salary
- Discretionary group performance-based bonus
- 25 days annual leave (plus Bank Holidays)
- Single cover private medical insurance
- Pension scheme
To make this a reality, we actively work to better represent the communities we operate in, foster inclusion, and establish fair processes. Through these actions, we build the trust needed for all colleagues at Drax to contribute their perspectives and talents, no matter their background. news.
confidential chat to discuss the role in more detail, please email careers@drax.