Senior Manager AI/ML

Full time Machine Learning Artificial Intelligence Software Engineering Data Warehouse

Job Description

EnerSys is the global leader in stored energy solutions for industrial applications. We have over thirty manufacturing and assembly plants worldwide servicing over 10,000 customers in more than 100 countries. Worldwide headquarters are located in Reading, PA, USA with regional headquarters in Europe and Asia. We complement our extensive line of Motive Power and Energy Systems with a full range of integrated services and systems. With sales and service locations throughout the world, and over 100 years of battery experience, EnerSys is the power/full solution for stored DC power products.

Job Purpose

EnerSys is at the forefront of revolutionizing DC Fast Charging Infrastructures, Microgrids, and Industrial Battery Solutions through artificial intelligence. If you enjoy shaping the future of product innovation as a core leader, driving value for customers, guiding successful launches, and exceeding expectations. Join our dynamic team and make a meaningful impact by delivering high-quality products that resonate with customers.

Our AI team leverages cutting-edge technologies, including Deep Learning, Reinforcement Learning, Optimization, and Machine Learning, to address complex challenges such as Energy Cost Optimization, Predictive Maintenance, Battery Health Estimation, and Time Series Forecasting. We are expanding our horizons into Large Language Models (LLMs) and Generative AI (GenAI), pushing the boundaries of AI-powered solutions.

The AI design Team for Software Engineering focuses on creating business value by using advanced analytical and data-driven approaches to identify, prioritize and accelerate high-value opportunities that will help drive grid resilience, optimize asset lifecycles while improving operational economics.

Essential Duties and Responsibilities

In this role, you will drive towards a shared vision to build scalable, secure, and advanced data and analytics capabilities using AI/ML technologies. Drive the product roadmap for automating and augmenting decision making using advanced models, frameworks, and applications - Collaborate with technology partners and internal engineering teams on data architecture, standardization, and execution of the prioritized use-cases

The candidate will work closely with different stakeholders (project managers, system architects, data scientists, data engineers and AI/ML engineers) to formulate recommendations for improvements and enhancements aimed at using innovative engineering solutions.

Qualifications

  • PhD or MS in Computer/Data Science, Machine Learning, Mathematics or relevant field
  • A minimum of five (5) years of related experience AI/ML engineering manager
  • In-depth knowledge of Azure DevOps services, including Azure Pipelines, Azure Machine Learning, and Azure Artifacts Experience with Design, implement, and maintain CI/CD pipelines
  • Deep knowledge with object-oriented/object function scripting languages: Python, Java, C++ etc.
  • A demonstrable understanding of networking/distributed computing environment concepts
  • Experience TensorFlow, Caffe, OpenCL or any Machine Learning and Data Science framework is a plus.
  • Knowledge and experience in IP communication (Websocket, MQTT…) and minimum two of CAN, I2C, SPI, RS232/485
  • Deep knowledge of SQL databases and ability to execute queries quickly.
  • Knowledge of data warehousing and data modeling.
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

EnerSys provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. EEO/Minority/Female/Vets/Disabled