Machine Learning Automation Engineer

Atlas Roofing Corporation
US - Mississippi - Madison
January 5, 2025
Manufacturing

Atlas Web Technologies a Division of Atlas Roofing Corporation focuses on the development and manufacture of state-of-the-art substrate product solutions for the building, construction, lamination, and original equipment management (OEM) industries.
The solutions are derived from the three primary technologies:
recycled paper, coated non-wovens, and hybrids of these base technologies.
Atlas Web Technologies products are suitable for everything from packaging to roofing underlayments, buildings to automobiles, furniture table pads to lamination.

Atlas Roofing Corporation, a privately owned company, established in 1982, is an international and multi-divisional manufacturer of roofing, sheathing, facer, and insulation product solutions.

Atlas is seeking a highly skilled Machine Learning Automation Engineer for the Meridian, Mississippi facility.

• PLEASE DO NOT APPLY IF YOU REQUIRE A VISA SPONSORSHIP OR A TRANSFER.

• We do not sponsor Visa's at Atlas Roofing Corp.

The Machine Learning Automation Engineer will have a strong background in database administration, data mining, machine learning, and SCADA systems.
Must have experience with machine learning frameworks and Automation Ignition scripting experience along with programming languages such as Python, R, MS SQL and Oracle SQL. This role requires excellent technical skills, attention to detail, and the ability to work collaboratively with cross-functional teams to optimize industrial processes and enhance data-driven decision-making.

Machine Learning Automation Engineer Essential Job Duties and Responsibilities

Database Administration:
Manage and maintain industrial databases, ensuring data integrity, security, and availability.
Perform regular backups, updates, and performance tuning.
Data Mining:
Extract and analyze large datasets from various industrial sources to identify patterns, trends, and insights that drive process improvements and operational efficiency.
SCADA Systems:
Implement and manage SCADA (Supervisory Control and Data Acquisition) systems for real-time data acquisition, monitoring, and control of industrial processes.
Data Integration:
Integrate data from multiple sources, including SCADA systems, databases, and external data feeds, to create comprehensive datasets for analysis and machine learning applications.
Performance Monitoring:
Continuously monitor and evaluate the performance of databases, machine learning models, and SCADA systems, making necessary adjustments to improve accuracy and efficiency.

Machine Learning Automation Engineer Knowledge Skills and Abilities

Experience with industrial automation and control systems.
Knowledge of real-time data acquisition and processing.
Familiarity with cloud platforms and big data technologies.
Machine Learning:
Design, develop, and deploy machine learning models to predict and optimize industrial processes, ensuring high accuracy and reliability.

Machine Learning Automation Education and Must Have Experience

Bachelor's degree in data science, computer science, or a related field.
Proficiency in programming languages such as Python, R, MS SQL and Oracle SQL is a must have.
Inductive Automation Ignition scripting experience is a must-have.
Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, and Scikit-Learn is a must have.
Strong analytical and problem-solving skills, with the ability to work with large and complex datasets.
Excellent communication and collaboration skills, with the ability to work effectively in a team environment.

Total Compensation

Atlas Molded Products offers competitive compensation and vacation/holiday package as well as a comprehensive benefits program including Medical, Dental, Vision, Disability, Life/AD&D/LTD insurance, 401k and Medical & Dependent Care Spending Accounts.

Atlas Roofing Corporation is an Equal Employment Opportunity Employer

No calls or agencies please.

Read the full job description and apply online on the recuiter's web-site

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