Amplify Cell Technologies is seeking to transform how data and artificial intelligence shape the future of EV battery manufacturing by leveraging advanced analytics and AI to drive operational excellence, optimize product quality, enable predictive maintenance, and fuel research and development.
Requirements
- Proficiency with data modeling, database management (SQL and NoSQL), and ETL processes.
- Extensive experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn), and data analytics platforms (e.g., Databricks, Spark, Hadoop).
- Practical knowledge of IoT integration and handling time-series sensor data in industrial settings.
- Experience in cloud technologies and services (e.g., AWS, Azure, GCP) for data storage, processing, and AI model deployment.
- Experience in establishing data governance protocols and ensuring regulatory compliance.
- Experience in programming languages such as Python, Java, or Scala.
- Proven ability to design end-to-end AI-driven solutions for process optimization, predictive maintenance, or quality control.
Responsibilities
- Design and implement robust data architectures that enable real-time analytics, data integration, and seamless information flow across the organization.
- Develop a scalable and secure data ecosystem that supports enterprise-wide analytics and AI applications.
- Define AI strategies, identify opportunities for AI implementation, and align AI initiatives with business objectives.
- Design enterprise AI architecture, including data pipelines, machine learning models, and integration with existing infrastructure with focus AI/ML solutions tailored to enterprise productivity improvements and battery manufacturing processes, including predictive maintenance, quality assurance, process optimization, and yield improvement.
- Establish data governance frameworks, ensuring data quality, consistency, integrity, privacy, and compliance with industry standards (e.g., ISO, GDPR, industry-specific regulations).
- Integrate data from diverse sources such as manufacturing equipment, IoT sensors, ERP systems such as SAP, and supply chain platforms to enable a connected, data-rich environment.
- Architect systems to manage and process large-scale data efficiently, ensuring high availability, reliability, and performance for real-time and batch operations.
Other
- Bachelors degree in Computer Science, Data Science, Engineering, or a related field; Masters degree preferred
- 10+ years of experience in the Information Technology field, with a minimum of 7 years of experience in data architecture, data engineering, or AI solution development, preferably in a manufacturing or industrial environment.
- Excellent communication skills and the ability to engage technical and non-technical stakeholders effectively.
- Ability to envision and realize novel applications of data and AI in a manufacturing context.
- Capability to lead cross-functional teams and champion data and AI initiatives across department.
