Backend Engineer, Machine Learning - Singapore - Grab

Grab

Verified Company

Singapore

1 week ago

Posted by:

Wei Jie

beBee Recruiter

Description

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

The Fulfilment tech family is one of the most important pillars enabling Grab to out-serve our customers and partners in different businesses and marketplaces across Southeast Asia.

We are working on high throughput, real-time distributed systems that use sophisticated machine learning techniques to solve hundreds of millions of requests per day.

Our mission is to offer the best-in-class products and experiences to our driver partners as to increase adoption and engagement of our services.

Improve driver partner opportunities and efficiency in order to fulfil customer orders without fail, rain or shine.

And to create efficient marketplaces by determining an optimal price that is both sustainable and loved by our partners and customers.

Currently our team members are in Indonesia, Malaysia and Singapore.

Get to know the Role
We are seeking talented & passionate Engineers to join our team.

You will have opportunities to work with a small team of engineers to work on multiple backend service clusters as well as participate in building machine learning pipelines.

It is very important that our team members take the initiatives to identify problems and have the right mindset and skill sets to solve them.

The Day-to-Day Activities

Lead project development as engineering owner of a group of 3~5 engineers, working closely with product managers to understand the requirements, propose solutions and coordinate dependencies
Design and write with the cutting edge GO language to improve the availability, scalability, latency, and efficiency of Grab's range of services
Engage in service capacity and demand planning, software performance analysis, tuning, and optimization
Work closely with infrastructure team in building and scaling backend services as well as performing root cause analysis investigations
Work closely with mobile team to build reusable modularized mobile components utilising scalable APIs
Collaborate with product and experience teams to finalise feature specifications, build prototype and design experiments.
Work with different engineering teams to explore and create new design/architectures geared towards scale and performance
Participate in code and design reviews to maintain our high development standards
Join oncall rotations to debug production issues and improve system stability.

The Must-Haves
Technical Must Haves

Working experience on backend development for 1~3 years
Strong computer science fundamentals in algorithms and data structures
Handson familiarity with running large scale distributed web or api services; understanding of systems internals and networking is a plus
Handson familiarity with database and at least one data query languages like mysql or Presto
Strong understanding of system performance and able to do profiling to find system bottlenecks
Strong understanding and experience on cloud platforms like AWS, GCP, Azure
Strong understanding of testing frameworks for unit testing, integration testing and E2E testing
Handson familiarity with CI/CD pipelines for system development and deployment
Experience with highspeed distributed computing frameworks like Apache Flink.
You can be a good coder in any language (C++, C, Java, Scala, Rust, Haskell, OCaml, Erlang, Python, Ruby, PHP, Node.

JS, C#, etc.), but willing to work on Golang and Scala (Flink)

Soft Skills Must Haves

Fluent in spoken and written English
Good communication skills, and have an proactive mindset
Able to think critically of the current system in terms of growth and stability

The Nice-to-Haves

Experience with Kubernetes, Dockers is a plus.
Experience with building machine learning pipelines, optimising model performance.
Experience with geospatial based algorithms and APIs like OpenStreet Maps or Google Maps.
A degree in Computer Science, Software Engineering, Information Technology or related fields.

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.