Job Title: Machine Learning Engineer (Manufacturing)
Key Responsibilities
Design, build, and deploy machine learning models for manufacturing use cases
Develop and maintain end-to-end ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment.
Prepare & curate training datasets with domain SMEs
Collaborate with cross-functional teams including:
Manufacturing engineers
Process engineers
IT / OT teams
Data scientists and analysts
Integrate ML solutions with production systems (e.g., MES, SCADA, IoT platforms).
Own feature engineering & data pipeline reliability
Prepare & curate training datasets with domain SMEs
Monitor model performance in production and implement retraining and continuous improvement processes.
Work with structured and unstructured industrial datasets (sensor data, time series, images).
Ensure solutions are scalable, reliable, and aligned with best practices in MLOps.
Document models, pipelines, and processes to support maintainability and knowledge transfer.
Desired Qualifications
Bachelor’s or Master’s degree in:
Computer Science
Data Science
Engineering (Mechanical, Industrial, Electrical, or related)
Or equivalent practical experience
~5 years of experience in machine learning engineering or applied data science.
Proven experience in a manufacturing, industrial, or IoT environment.
Technical Skills
Strong understanding of supervised and unsupervised learning techniques
Experience with time-series analysis and anomaly detection
Familiarity with computer vision applications (preferred)
Model evaluation, validation, and tuning
Programming & Tools
Proficiency in Python
Experience with ML libraries such as:
TensorFlow / PyTorch
Scikit-learn
Strong SQL skills and experience with large datasets
Experience deploying models securely into production environments
Familiarity with:
Model monitoring and versioning
Experience with data pipelines and ETL processes
Exposure to cloud platforms (AWS, Azure, or GCP)
AI Tools
Proficient with AI Tools and Assistants (e.g. Claude, ChatGPT, GitHub Copilot) for development and research
Strong problem-solving skills with a practical, results-driven mindset
Ability to translate business and operational problems into ML solutions
Collaborative team player with cross-functional experience
High attention to detail and data quality
Ability to breakdown work into deliverables
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