ML Engineer: Edge AI for Low-Carbon Plants

Gigaton; Greater London; Vor Ort; GBP 60.000 - 120.000; Vollzeit

Benefits dieser Stelle

Equity

Flexible working

30 days holiday

Pension scheme

Zusammenfassung

Gigaton is building autonomous AI control for heavy industries to cut CO2 emissions. As a Machine Learning Engineer (mid to principal), you will develop models that underpin our control systems and scale our ML infrastructure.

You’ll work across research and deployment, collaborating with scientists and engineers, using Python, PyTorch and scikit-learn on cloud platforms. Equity, flexible working and generous holidays accompany a mission-driven culture.

Qualifikationen

• 2+ years of experience as a machine learning engineer.
• Experience with ML techniques and implementing different solutions.
• Proficient in Python and ML libraries (scikit-learn, PyTorch).
• Experience deploying end-to-end ML solutions in production.
• Experience in scientific environments across disciplines is a plus.
• Interest in climate impact and Gigaton’s mission.

Aufgaben

• Build state-of-the-art systems combining edge control with active learning to reduce CO2 emissions.
• Work in the ML team as an individual contributor, building, testing and deploying models, optimisers and controllers.
• Contribute to technical innovation and problem-solving across the ML lifecycle.
• Collaborate with cross-functional teams on customer projects and product development.
• Help establish best practices to improve internal processes.
• Design robust, maintainable and scalable ML systems.

Kenntnisse

Python

ML algorithms

End-to-end deployments

Team collaboration

Ausbildung

Degree in machine learning, physics, chemistry, engineering, mathematics or computer science

Tools

scikit-learn

PyTorch

TensorFlow

AWS/GCP/Azure

Jobbeschreibung

Gigaton is building autonomous AI control for heavy industries to cut CO2 emissions. As a Machine Learning Engineer (mid to principal), you will develop models that underpin our control systems and scale our ML infrastructure.

You’ll work across research and deployment, collaborating with scientists and engineers, using Python, PyTorch and scikit-learn on cloud platforms. Equity, flexible working and generous holidays accompany a mission-driven culture.