Machine Learning Engineer

World’s leading logistics group and supply chain that operates on a cutting-edge analytics platform.
Your new company
World’s leading logistics group and supply chain that operates on a cutting-edge analytics platform.

They are looking for a Machine Learning Engineer to undertake data science models, expanding scalability to advanced production level models.

Your new role
  • Be able to work with team members to ensure delivery of analytics best practices within ML solutions and MLOps requirements.
  • Maintain, implement, design and develop the end to end of the ML pipeline.
  • Agility to evolve ML solutions and perform multiple deployments concurrently
  • Have stakeholder management skills and keep to project milestones.

What you'll need to succeed
  • At least 4 years or relevant experience in Data, DevOps, or Machine Learning.
  • Working experience in ML Ops and deployment.
  • Have experience in data structures, ML architecture, modelling and algorithms.
  • Good presentation skills, collaborative work with cross function or global teams with good business acumen.
  • Proficient in Python, Tensorflow, Keras, SQL, Flask, Java/Springboot
  • Have experience with Airflow, MLFlow
  • Understanding of DevOps, Agile, Cloud environment is a plus.

What you'll get in return
  • Competitive remuneration
  • Work with cutting edge technologies
  • Make impact in a dynamic global organization in their leading field

What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV. If this job isn't quite right for you but you are looking for a new position within Technology, please contact Lijie Ong at +65 81006059 or email for a confidential discussion on your career.

Hays Registration Number: R22108533, EA License: 07C3924, Company Registration Number: 200609504D. #1225037


Job Type
Supply Chain & Logistics
Supply Chain

Talk to a consultant

Talk to LiJie Ong, the specialist consultant managing this position, located in Singapore
#27-20 UOB Plaza 2, 80 Raffles Place

Telephone: 63030158

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