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Machine Learning Engineer
Machine Learning EngineerSephora • Singapore, Singapore
Machine Learning Engineer

Machine Learning Engineer

Sephora • Singapore, Singapore
30+ days ago
Job description

Profile

At Sephora, beauty is about feeling seen, valued, and empowered, individually and collectively. It is connecting deeply with others, celebrating diversity and inclusivity, unlocking your potential and making a difference every day. Together, we belong to something beautiful.

Sephora SEA’s omni channel business spans over 8 countries (Australia, India, Indonesia, Malaysia, New Zealand, the Philippines, Singapore and Thailand) with 100+ stores and boasts some global flagships such as ION and Raffles City in Singapore, F88 in Kuala Lumpur and Pitt Street in Sydney. Sephora SEA is experiencing rapid growth in the region with new store openings and business channels (., Click and collect and marketplace).

Machine Learning Engineer

We are looking for a passionate and highly skilled Machine Learning Engineer to join our team and shape the future of beauty Ecommerce in Southeast Asia. In this role, you will report to the Manager, Machine Learning Engineering in the tech organization and be part of a highly collaborative team delivering and deploying robust ML models and LLM-based applications to production environments. This high impact role will be directly responsible to build and update our ML and AI applications that power multiple high-touch consumer experiences across our native mobile app, website, and in-store across all countries in SEA, ANZ and India, with collaboration on key topics with global MLE teams in Europe, China and US.

You will shine here if you enjoy...

  • Architecting, developing, training and deploying production, real-time Machine Learning (ML) applications
  • Using deep learning frameworks such as PyTorch / Torch lightning to develop and iterate on ML models such as recommendation engines, NLP, Computer Vision, etc while ensuring datasets are relevant, complete, and picking suitable model architecture to fit business needs
  • Using high performance Python frameworks like FastAPI or LitServe 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 Big Query
  • Leveraging open source LLM Agent frameworks to design and develop LLM Agents and workflows, choosing between pure prompt-engineering and fine-tuning when needed
  • Continuously improving the performance of deployed ML and AI applications by researching and implementing advanced ML techniques and new AI capabilities, with a focus on areas like recommendation engineers, reinforcement learning and Agentic AI
  • Collaborating with scrum master, product manager, data engineer, and peers to define and secure clean, scalable data sources using advanced Big Query SQL for model training and evaluation
  • Staying on top of the latest developments in Data Science, Artificial Intelligence and Machine Learning spaces, continuously bringing new state-of-the-art techniques to solve various business and customer problems

We would love to hear from you if you are/have…

  • At least 5 years of experience building and scaling real-time production ML applications, transformer model experience is a plus
  • Strong proficiency in ML orchestration tools like Kubeflow Pipelines, Airflow, ZenML, etc and ML frameworks like Pytorch with a proven track record in setting up MLOps pipelines and deploying ML models to production
  • Strong Python programming knowledge and experience in API frameworks such as FastAPI, Severless cloud computing knowledge on GCP is a plus
  • Familiarity with dataset curation through BigQuery SQL, DBT, and pre-processing using PySpark / Polars
  • A demonstrated ability to understand and translate business requirements into ML applications, past experience working on real-time recommendation engines and reinforcement learning is a plus
  • Ability to connect the dots between technical data science / machine learning technologies and business context

Here, you will find:

  • Community, in which authenticity is embraced, and the strength of our differences fuels our collective spirit
  • Culture of empowerment, learning & growth, that offers you the tools, space and opportunity to learn, innovate and lead
  • Work that brings fulfilment, from delighting clients every day, to inspiring our industry at large, every action makes a difference

It is in the Sephora DNA to champion a world of inspiration and inclusion where everyone can celebrate their beauty. You can be yourself, because you are what sets us apart. Join us and belong to something beautiful.

Sephora is proud to be an equal opportunity workplace for all. We do not discriminate in recruitment, hiring, training, advancement, or other employment practices. We celebrate diversity and are committed to creating and fostering an inclusive environment for all employees.

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Machine Learning Engineer • Singapore, Singapore

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