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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 (e.g., 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 lifecycle
- 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.
