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Tier-1 employer, metro location, mid-level ML generalist, and broad skillset increase applicant competition.
Machine learning skills are broadly transferable across industries but require domain adaptation.
Explicit 2–5 years requirement and mandatory ML experience create moderate filtering.
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Implement and manage machine learning algorithms including model training, validation, and deployment in production environments.
Design and develop data pipelines with focus on data ingestion, validation, cleaning, and monitoring.
Research and contribute to technical documentation, patents, APIs, case studies, proof of concept designs, and evaluations of ML solutions.
Bachelor's degree or equivalent combination of coursework and experience.
2-5 years of relevant work experience in machine learning or related field.
Ability to work nights and weekends with variable schedule as necessary.
Regular attendance and capability to exercise independent judgment on significant matters.
Experienced in end-to-end machine learning lifecycle including algorithm implementation, model deployment, and data pipeline engineering.
Able to contribute to research and innovation including producing technical documentation, patents, and proof of concepts.
Comfortable with variable working hours and autonomous decision-making in a technology-driven environment.