Machine Learning Engineer

Reposted 13 Hours Ago
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DKI Jakarta, IDN
In-Office
Mid level
Fintech • Payments • Financial Services
The Role
The Machine Learning Engineer at Kredivo will develop ML pipeline infrastructure, collaborate with Data Scientists on predictive models, and ensure maintainable data science code.
Summary Generated by Built In

At Kredivo we are building the future of financial services that are fast, cheap and widely accessible, wrapped up in a beautiful UX. As we are growing bigger, we are looking for Machine Learning Engineer who will closely collaborate with Data Science team in feeding data (across functions such as, credit scoring, fraud, and risk) into financial models defined by data scientists. You will also be responsible to make sure that data science code is maintainable, scalable and debuggable.

Job Responsibility

  • Develop and implement ML pipeline infrastructure, including but not limited to: ETL (Extract, Transform and Load) of raw data into model features and building platform to automate ML training, testing and maintenance.
  • Partnering with Data Scientists to transform prototypes of predictive models into high performance, well integrated systems.

Qualifications

  • 2-3 years of relevant experience in Data or Software Engineering and minimum 1-2 years hands-on experience in deploying machine learning models and feature pipelines
  • Having good knowledge of data structures, data modeling and software architecture related to Machine Learning
  • Ability to write robust production-ready code in Python & GoLang
  • High degree of proficiency with RDBMS (i.e. MySQL, PostgreSQL) and No-SQL platforms (i.e. S3)
  • Proficiency in machine learning libraries such as: Tensorflow/Keras, Pytorch, SparkML or MLeap
  • Strong interest in building scalable and reliable Machine Learning Engineering/AI related services
  • Past experience working with cloud services platform to build data pipelines, monitoring, scheduler and storage, preferably on AWS environment.
  • Familiarity using a distributed computing platform, such as Hadoop or Spark

Thank you for your interest in Kredivo. We’re thrilled that you’d like to join our company. Unfortunately, days are short and applicants are many, so we won’t have time to meet everyone. If you are among qualified candidates, you will receive a call or email from our Talent Acquisition team.

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Skills Required

  • 2-3 years of relevant experience in Data or Software Engineering
  • 1-2 years hands-on experience in deploying machine learning models and feature pipelines
  • Good knowledge of data structures, data modeling and software architecture related to Machine Learning
  • Ability to write robust production-ready code in Python & GoLang
  • High degree of proficiency with RDBMS and No-SQL platforms
  • Proficiency in machine learning libraries such as Tensorflow/Keras, Pytorch, SparkML or MLeap
  • Strong interest in building scalable and reliable Machine Learning Engineering/AI related services
  • Past experience working with cloud services platform to build data pipelines, preferably on AWS
  • Familiarity using a distributed computing platform, such as Hadoop or Spark
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The Company
1,707 Employees

What We Do

Kredivo Group is Southeast Asia’s leading provider of digital financial services through its brands Kredivo, KrediFazz and Krom. Kredivo is the leading digital credit platform in Indonesia and Vietnam that gives customers instant credit financing for ecommerce and offline purchases, and personal loans, based on real-time decisioning. Kredivo users can buy now and pay later across the entirety of Indonesia’s retail commerce network with one of the lowest interest rates amongst digital credit providers in the country. Krom Bank Indonesia (formerly known as Bank Bisnis Internasional, IDX: BBSI) is the group’s bank entity and the operator of the Indonesian neobank Krom. Kredivo Group is backed by leading financial and strategic investors such as Mizuho Financial Group, Square Peg Capital, Jungle Ventures, Naver Corp, Mirae Asset, Telkom Indonesia and Victory Park Capital among others

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