Lead Machine Learning Engineer
London - Hybrid
£80,000 - £95,000 + Bonus + Pension + Car Scheme + Technology Benefits + EAP Programme + Flexible working
This is an incredible opportunity for a Lead ML Engineer to join a fast paced and forward-thinking business always looking to innovate and lead from the front in the technology world.
The company are a leading organisation in the energy sector, dedicated to delivering innovative solutions and improving operational efficiency. As part of their Data Science team, you will be at the forefront of cutting-edge projects, helping to shape the future of data-driven decision-making and machine learning infrastructure.
In this role, you will lead machine learning projects from concept to production, develop platform tools, and collaborate with data scientists to build data pipelines. You'll mentor junior team members, work with IT teams to advance projects, and improve deployment processes.Additionally, you'll design and maintain cloud infrastructure, ensure high-quality code, and participate in code reviews.
The ideal candidate will have hands-on industry experience in software engineering, machine learning engineering, data science, DevOps, and cloud infrastructure. They will be highly proficient in Python, including libraries such as Pandas and scikit-learn, and possess strong SQL skills.A deep understanding of software engineering best practices and hands-on experience with tools like Azure, GitHub Actions, Terraform, Packer, Airflow, Docker, Kubernetes, and Linux/ Windows VM administration is essential.
An incredible opportunity for a confident and commercial ML Engineer to lead from the front working with cutting edge technology and driving company growth.
The Role:
- Lead machine learning projects from concept to production.
- Develop platform tools and collaborate with data scientists to build data pipelines.
- Mentor junior team members and support their technical growth.
- Work closely with IT teams to advance project goals and improve deployment processes.
- Design and maintain cloud infrastructure to support machine learning initiatives.
- Ensure high-quality code and actively participate in code reviews to maintain code quality. ul>
The Person:
- Hands-on industry experience in software engineering, machine learning engineering, data science, DevOps, and cloud infrastructure.
- Proficiency in Python, including libraries such as Pandas and scikit-learn, and strong SQL skills.
- Deep understanding of software engineering best practices.
- Experience with tools like Azure, GitHub Actions, Terraform, Packer, Airflow, Docker, and Kubernetes.
- Expertise in Linux/ Windows VM administration.
- Solid knowledge of modern security and networking principles. ul>