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minden.ai

Machine Learning Engineer/Lead

Department
Engineering
Job Type / Location
onsite
Experience Required
3+ years
Posted On

About the Role

minden.ai is a technology venture founded by Temasek in strategic partnership with DFI Retail Group and coalition partners. They are on a mission to redefine how brands engage with their customers through the power of machine learning and artificial intelligence, building a next-generation insights-driven platform to serve millions of customers and merchant partners across Southeast Asia.

The company is currently hiring multiple roles for the Machine Learning Engineering team. The ideal candidate will have a strong understanding of Machine learning concepts and Machine learning Operations.

Responsibilities as a Machine Learning - Engineer/Lead Level

  • Design and deliver a ML-based pricing system that delights our customers with a hyper-personalised experience.
  • Work closely with data scientists, data engineers and platform engineers to operationalise ML models and serve inferences efficiently, which include automating ML pipelines, performance monitoring and testing.
  • Collaborate with product owners and work backwards from both our customers and partners to define AI/ML features.
  • Be the evangelist for AI/ML through mentoring and technical/knowledge sharing.
  • Participate actively in design and code reviews.
  • Lead, coach and mentor a high-performing Machine Learning team (For lead role)

Requirements

  • A bachelor’s degree in Computer Science, Data Science, IT or a related discipline.
  • Possess at least 3-8 years of experience in software engineering or ML engineering.
  • Minimal 3 years experience in leading a ML team (For Lead role).
  • Programming experience in Python, Java, Pyspark and Scala.
  • Possess knowledge of Big Data frameworks like Hadoop, Spark, Impala, Hive, etc.
  • Experience in building and optimizing Machine Learning models, pipelines and architectures.
  • Experience with ML frameworks such as TensorFlow, Keras, PyTorch.
  • Basic understanding of ML concepts.
  • Strong hands on coding experience.
  • Strong understanding and experience in ML Ops.
  • Experience in putting ML model into production.
  • Experience working in an agile startup environment.

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