Machine Learning Engineer
Perx Technologies provides a fully integrated solution that combines a next-generation SaaS loyalty management system and omni-channel marketing technologies to deliver revenue-driving digital customer experiences.
The Perx Loyalty and Customer Engagement platform allows large B2C enterprises to drive meaningful digital customer experiences targeted at millions of customers. The A.I. enabled platform is trusted by the likes of UOB, HSBC, Central group, AXA, Prudential, Digi, among others in the South East Asian and European markets to drive revenue.
We’re a company that understands that product innovation comes from people innovation, and that’s why we invest in cultivating leaders and HIPOs throughout the organization. If you’re passionate about creating and contributing to a top-notch culture and talent pool, join us!
We are looking for a Machine Learning Engineer who will help us discover the information hidden in vast amounts of data, and to define meaningful user journeys for our enterprise customers. Your primary focus will be on building end to end machine learning workloads deployed in the cloud. This role works closely with our Data team and Engineering team to develop ETL pipelines, experiment with different ML models, deploy ML workloads as API services and integrate with our existing core API platform.
Candidates should have deep understanding of machine learning life cycle and how to turn hypotheses into production systems.
What’s the role?
- Build pipelines to processing, transform data to fit ML workloads.
- Leveraging cloud ML services to build high-quality ML projects specific to platform needs
- Review constantly for performance improvement and decide which ML technologies can be used in a production environment
- Ensure high performance of overall production tasks in terms of actual execution and scheduling
- Upkeep data science code for future maintenance, scalability and debugging
- Automates and optimise repeated routines in machine learning tasks
- Chooses best operational architecture together with devops team
- Work closely with data team and engineering team to deliver end to end working machine learning projects.
- Apply modern industry standard development practices around version control, testing etc.
- Collaborate with research engineers to recommend improvements to data collection and experimental strategy to optimise system performance.
- Characterise classifier or algorithm performance against defined project objectives; proposed implementation environment; and associated computational constraints.
Who are we looking for?
- Proficiency with one or more state of the art Machine Learning frameworks such as TensorFlow, Keras, PyTorch, Skicit-learn, etc.
- Proficiency with Python and basic libraries for Machine Learning such as numpy, pandas, scipy, jupyter notebook, matplotlib, etc.
- Exposure to machine learning algorithms, deep learning and big data processing tools.
- Exposure to at least one state of the art big data tools like kafka, apache beam and cloud warehouse services like BigQuery is preferred.
- Experience with cloud machine learning services on either AWS or GCP like Google Cloud ML Engine or SageMaker is prefered.
- Ability to breakdown data science scope into workable tasks that can be shared across the engineering team.
- MS/BS in Computer Science, Mathematics, Physics or equivalent work experience.
- Must have work experience in backend development (Java, Python, Go, etc)
- Familiar with Git, Linux
What’s on offer?
- Collaborative environment and the opportunity to work with one of Asia’s leading players in the Martech and Fintech space.
- Opportunity to work with > 1Bn B2C global conglomerates in the banking, large retail, insurance and telecom sectors.
- Work with a globally hand-picked talent of 60+ employees who power some of the largest brands in the region who leverage the SaaS platform to engage with 50Mn+ consumers each day.
- Great career development opportunities across marketing, pre-sales and customer engagement teams offered with cross developmental training.