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Tier-1 brand, mid-level ML role, and broad skillset create high competition.
Core ML engineering skills are broadly transferable across industries, so background sensitivity is low.
Explicit 5–7 years requirement plus mandatory ML engineering and deployment experience increases screening rigor.
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Develop, validate, and deploy machine learning algorithms and models into production.
Design and implement data pipelines for data ingestion, validation, cleaning, and monitoring.
Research and document technical requirements, evaluate internal and external ML solutions, and provide technical leadership to junior engineers.
Bachelor's Degree (preferred; equivalent coursework and experience considered).
5-7 years of relevant work experience in machine learning or related fields.
Ability to work nights, weekends, variable schedules, and overtime as necessary.
Experience in developing and deploying machine learning models and data pipelines.
Experienced practitioner with proven ability to independently prioritize and lead ML engineering tasks.
Strong collaborator capable of working across teams and guiding junior engineers.
Demonstrates technical depth in machine learning algorithm development and operational deployment in production environments.