Sephora

5 months ago

Machine Learning Engineer (Singapore, SG)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 9 hours agoStatus: Live

Job Summary

The role builds and deploys real-time ML applications for Sephora’s beauty ecommerce platform across SEA, ANZ, and India. You will own end-to-end ML lifecycle—from data extraction and feature engineering to training, evaluation, deployment, and retraining—using PyTorch, Kubeflow Pipelines on GCP, and real-time serving with FastAPI, collaborating with cross-functional teams to deliver scalable ML solutions.

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Architecting, developing, training and deploying production, real-time Machine Learning (ML) applications.
•Using high performance Python frameworks like FastAPI to serve real time ML models with high throughput and low latency.
•Managing the end-to-end ML lifecycle, including data extraction, feature engineering, model training, performance monitoring, deployment, and continuous retraining using Kubeflow Pipelines on GCP VertexAI, Cloud Run and BigQuery.
•Leveraging open source LLM Agent frameworks to design and develop LLM Agents and workflows, choosing between prompt-engineering and fine-tuning when needed.
•Collaborating with scrum master, product manager, data engineer, and peers to define and secure clean, scalable data sources using advanced BigQuery SQL for model training and evaluation.

Key Requirements

•At least 5 years of experience building and scaling real-time production ML applications.

Experience:5+ yearsEcommerceRetail

Skills:CollaborationCommunicationProblem-solving

Tech Stack:PyTorchTorchLightningFastAPILitServeKubeflow PipelinesVertexAICloud RunBigQueryDBTPySparkPolarsLLMAgent frameworksGCP

Company Brief

Sephora

Global retailer of cosmetics, skincare, fragrance and beauty accessories operating physical stores and e-commerce. Sephora offers multi-brand product assortments, in-store services, and digital experiences and is a subsidiary of LVMH.

Industry: Omnichannel Retail

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Headquarters: Paris, France

Founded: 1969

Website LinkedIn

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Sephora

5 months ago

Machine Learning Engineer (Singapore, SG)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 9 hours agoStatus: Live

Job Summary

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•Architecting, developing, training and deploying production, real-time Machine Learning (ML) applications.
•Using high performance Python frameworks like FastAPI to serve real time ML models with high throughput and low latency.
•Managing the end-to-end ML lifecycle, including data extraction, feature engineering, model training, performance monitoring, deployment, and continuous retraining using Kubeflow Pipelines on GCP VertexAI, Cloud Run and BigQuery.
•Leveraging open source LLM Agent frameworks to design and develop LLM Agents and workflows, choosing between prompt-engineering and fine-tuning when needed.
•Collaborating with scrum master, product manager, data engineer, and peers to define and secure clean, scalable data sources using advanced BigQuery SQL for model training and evaluation.

Key Requirements

•At least 5 years of experience building and scaling real-time production ML applications.

Experience:5+ yearsEcommerceRetail

Skills:CollaborationCommunicationProblem-solving

Tech Stack:PyTorchTorchLightningFastAPILitServeKubeflow PipelinesVertexAICloud RunBigQueryDBTPySparkPolarsLLMAgent frameworksGCP

Company Brief

Sephora

Industry: Omnichannel Retail

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Headquarters: Paris, France

Founded: 1969

Website LinkedIn