Machine Learning Specialist (Battery)

Birmingham, West Midlands
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Our client, an innovative UK-based manufacturing business specializing in sustainable battery production for electric vehicles is currently hiring a Machine Learning Specialist. The successful candidate will be responsible for developing and implementing machine learning models to optimize battery performance, enhance manufacturing efficiency, and drive predictive maintenance strategies.
 
The Machine Learning Specialist will:

Apply computer vision and anomaly detection techniques for quality control in battery manufacturing.
Design and implement AI-driven process automation to enhance production scalability.
Develop, train, and deploy machine learning models to enhance battery performance, efficiency, and longevity.
Collaborate with cross-functional teams, including R&D, manufacturing, and software engineering, to integrate ML solutions into real-world applications.
Analyse large datasets from battery testing, manufacturing processes, and field performance to identify patterns and predictive insights.  
 
The Machine Learning Specialist will have:

Strong expertise in machine learning, deep learning, and data science methodologies.
Strong understanding of big data processing and cloud computing platforms (AWS, Azure, or GCP).
Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks.
Experience in deploying ML models to production using MLOps techniques.
A background in manufacturing analytics, industrial AI, or quality control applications is desirable.
Degree in Computer Science, Data Science, Electrical Engineering, or a related field (MSc or PhD preferred).  
Please apply using an up-to-date version of your CV and a member of the EVera team will contact you shortly to provide more details

Job Info
CV-Library logo
Job Title:
Machine Learning Specialist (Battery)
Company:
CV-Library
Location:
Birmingham, West Midlands
Salary:
Competitive
Posted:
Mar 20th 2025
Closes:
Apr 20th 2025
Sector:
Engineering
Contract:
Permanent
Hours:
Full Time
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