Job Description
ML Engineer/Machine Learning Engineer/Lead Engineer/Data Pipelines/Data Science/Models/Azure/Python/Pandas/SQL/Remote/Home based/Permanent/Salary £80,000 - 95,000 + 15% bonus + benefits.
One of our leading clients is looking to recruit a ML Engineer/Lead/Senior ML Engineer.
Location - Remote/Home based - may require occasional trip to London
Permanent role
Salary: £80,000 - 95,000 + 15% bonus + benefits
You will be responsible for developing data pipelines, taking data science prototype models to production, fix production bugs, monitor operations, and provision the necessary infrastructure in Azure.
Experience:
* Hands-on industry experience in some combination of Software Engineering, ML Engineering, Data Science, DevOps, and Cloud Infrastructure work.
* Expertise in Python which includes experience in libraries such as Pandas, scikit-learn. High proficiency in SQL.
* Combination of the following technologies: Python ecosystem, Azure (VMs, Web Apps, Managed Databases), GitHub Actions, Terraform, Packer, Airflow, Docker, Kubernetes, Linux/Windows VM administration, Shell Scripting (primary Bash but PowerShell).
* A solid understanding of modern security and networking principles and standards.
* Bachelor's or higher degree in Computer Science, Data Science, and/or related quantitative degree is preferred from an accredited institution.
Accountabilities will include:
* Leading Machine Learning projects end-to-end.
* Develop platform tooling (eg, internal conda library, CLI tool for project setup, and provisioning infrastructure) for the Data Science team.
* Work with data scientists to understand their data needs and put together data pipelines to ingest data.
* Work with data scientists to take data science model prototypes to production.
* Mentor and train junior team members.
* Work with internal IT teams (security, Cloud, Global Active Directory, Architecture, Networking, etc.) to advance the team's projects.
* Enhance code deployment life cycle
* Improve model monitoring frameworks
* Refine project operations documentation
* Design, provision, and maintain the cloud infrastructure needed to support Data Engineering, Data Science, Machine Learning Engineers, and Machine Learning Operations.
* Write high-quality code that has high test coverage.
* Participate in code reviews to help improve code quality.
Technologies/Tools: Python, Azure (Virtual Machines, Azure Web Apps, Cloud Storage, Azure ML), Anaconda packages, Git, GitHub, GitHub Actions, Terraform, SQL, Artifactory, Airflow, Docker, Kubernetes, Linux/Windows VMs.