Machine Learning Engineer
At a glance
Mid-level Machine Learning Engineering role at Kredivo Group. Jakarta · full-time.
Pay not stated Machine Learning Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Turn raw data into model features, then build systems that automate model training, testing and maintenance
- Convert data scientists’ predictive-model prototypes into high-performance systems that work well with other software
- Keep data science code easy to maintain, scale and debug
- Work with data scientists on information for credit scoring, fraud and risk models
What you bring
- You have two to three years in data or software engineering, including one to two years deploying ML models and feature pipelines
- You can write robust production code in Python and Go, and understand data structures, data modeling and ML architecture
- You know relational and non-relational data platforms, plus ML libraries such as TensorFlow, Keras or PyTorch
- You have used cloud services for pipelines, monitoring, scheduling and storage, and are familiar with Hadoop, Spark or another listed platform
Who this fits
This mid-level role is based in Jakarta. It suits an engineer who works with data scientists to put machine-learning models into production.
From the employer
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.