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Mid-level ML role, popular title and metro location increase candidate competition.
High due to clinical imaging focus and ML lifecycle experience requirement.
Explicit 4–6 year requirement plus mandatory deep learning and computer vision skills.
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Build, optimize, and enhance AI/ML systems focusing on predictive accuracy and real-world production deployment.
Develop ETL data pipelines, event monitoring pipelines, and real-time data processing frameworks with large clinical and image datasets.
Evaluate and implement new algorithms and technologies pragmatically to deliver measurable results in computer vision and data science projects.
4–6 years of experience in deep learning, computer vision, and image quality.
Proficient in Python programming and libraries including Numpy, Matplotlib, Pandas, and Scikit Learn.
Hands-on experience with Linux environment.
Work Experience Required: 4–6 years in relevant fields as specified.
Experienced in the full data science lifecycle from data collection to model serving, especially with computer vision challenges.
Practically oriented with the ability to translate research into scalable production systems.
Comfortable working independently on projects and making pragmatic technology decisions to ensure business impact.