Senior Machine Learning Engineer
1 day ago
**Job Description**:
**Life at Grab**
At Grab, every Grabber is guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles - the 4Hs: Heart, Hunger, Honour and Humility. These principles guide and help us make decisions as we work to create economic empowerment for the people of Southeast Asia.
**Get to know the Team**
**Get to know the Role**:
- Be involved in the end to end lifecycle of Machine Learning, understanding the Data Science journey and building the right tools for our users
- Develop tools and services that enable ML practitioners to build robust machine learning pipelines that adhere to the principles of continuous delivery
**The Day-to-Day Activities**:
- Build and maintain scalable and flexible model training frameworks using containerisation technologies such as Kubernetes, allowing users to run heterogeneous workloads using the right open source technologies
- Build and maintain a cost efficient model serving platform at scale, flexible and robust enough to scale up and down depending on traffic patterns
- Collaborate with data scientists and ML engineers from different functions to empower them to deploy their machine learning solutions to production to solve business problems
**The Must-Haves**:
- Bachelor/Master/PhD Degree in Computer Science, Math, EE or similar field.
- Minimum 2 years experience as a software engineer writing production code
- Solid software engineering and coding skills. In addition to Python, experience in at least one backend language like Go, Scala, Java, C++ or other is required
- Decent understanding of Machine Learning / Deep Learning and the existing frameworks such as Tensorflow and PyTorch
- Strong understanding of distributed ETL frameworks like Spark or Scalding
- Experience with cloud-based big data and machine learning services is a plus
- Self-motivated, curious, team-player, problem solver
- Detail-oriented and focused in a dynamic and fast-paced working environment.
**Our Commitment**
We are committed to building diverse teams and creating an inclusive workplace that enables all Grabbers to perform at their best, regardless of nationality, ethnicity, religion, age, gender identity or sexual orientation and other attributes that make each Grabber unique.
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