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ASF124 - MACHINE LEARNING ENGINEER

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ASF124 - MACHINE LEARNING ENGINEER

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IT

Middle/Senior

Remote

Full-time

Responsibilities

  • Optimize existing machine learning infrastructure built on a scalable, cost-efficient serverless architecture. Especially focusing on expanding our system's capacity to serve more machine learning models and business logic with ease.

  • Improve our personalized perfume recommendation system to boost key business metrics like customer engagement, conversion rates, repeat purchases, etc.

  • Develop scalable data pipelines that systematically aggregate unstructured data like user feedback, ratings, etc., and transform them into structured features to fuel perfume preference research.

  • Research innovative techniques like graph neural networks to uncover novel ways we can better capture an individual’s olfactory preferences through our quizzes and thus formulate perfumes they find uniquely captivating.

Requirements

  • At least 2 years of experience building, optimizing, and deploying machine learning systems to production.

  • Fluency in techniques for feature engineering, machine learning model development, A/B testing frameworks, and infrastructure automation workflows.

  • Strong analytical skills and demonstrated ability to translate research findings into solutions that deliver clear business impact.

  • Creativity to explore emerging methods in AI, especially in graph and recommender systems, that could advance how we personalize perfumes.

  • Good at English.

  • Technical Skills: A/B Testing; PyTorch; Kubernetes; AWS Services (S3, EC2, Lambda, SageMaker etc.); Google Cloud Platform

  • Models/Methods: Recommendation Systems; Graph Neural Networks; Tree-based Models; Feature Engineering

  • Deployment: CI/CD Pipelines; Model Monitoring; Model Drift/Degradation; Serverless Architectures

  • Other Relevant Terms: Personalization; Optimization; Data Pipeline Care and judgment to responsibly incorporate new intelligence that maintains data ethics and customer satisfaction as top priorities.

Benefits

Working location: Remote Full-time

Salary range: up to USD 2,300 NET

Infomation

Offered Salary

1,500 $ - 2,300 $

Skills

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