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Remote role, popular ML title, metro location and broad ML/MLOps requirements drive high applicant competition.
ML engineering skills transfer across industries but require specialized ML expertise, so medium sensitivity.
Explicit 2+ years plus mandatory Python, TensorFlow/PyTorch, cloud and SQL create moderately strict filters.
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Design, develop, deploy, and monitor machine learning models using Python and frameworks like TensorFlow, PyTorch, and scikit-learn.
Collaborate with data scientists and domain experts to translate business requirements into scalable ML solutions powering manufacturing sector.
Implement and maintain data pipelines and optimize models for performance and scalability in production environments.
Bachelor’s degree in Computer Science, Engineering, or related field.
2+ years of experience as an ML Engineer or similar role.
Proficiency in Python and machine learning libraries: TensorFlow, PyTorch, scikit-learn.
Familiarity with cloud platforms (AWS, GCP, or Azure) and proficiency in SQL with relational databases.
Experienced in end-to-end ML lifecycle including design, deployment, and monitoring in production-scale environments.
Ability to work cross-functionally with domain experts and data scientists effectively to deliver business impact through ML.
Comfortable with preprocessing large datasets, feature engineering, and optimizing model performance in real-world applications.