Tuyển dụng Data Scientist

The role at a glance

Skills you need

What we offer

Life at Grab

The role at a glance

The Data Science (Geo Vision) team improves Grab's maps and builds map-based intelligence (localization, routing, travel-time, traffic forecasting) using computer vision and deep learning on images, video, and GPS signals.

As a Data Scientist, you'll focus on bringing computer vision models to embedded/edge platforms for map creation. You will be working onsite and reporting to the Head of Data Science based in Cluj.

What you'll work on

Help adapt and improve CV models (detection, segmentation, tracking) to run on resource-constrained edge devices.

Apply model compression — quantization, pruning, knowledge distillation — to shrink models while preserving accuracy.

Profile on-device performance (latency, memory, power) and help build efficient inference pipelines.

Support training and evaluation, and use AI agents/tooling within the team's quality guidelines.

What you'll gain: hands-on experience taking deep learning models to on-device deployment, plus skills in model optimization and real-time edge performance.

Skills you need

Pursuing or recently completed a degree in Computer Science, Electrical Engineering, or a related field.

Familiarity with Python and some of: PyTorch/TensorFlow, NumPy, OpenCV, and scikit-learn.

Solid ML and deep learning / computer vision fundamentals.

Interest in or exposure to embedded systems, edge deployment, or model optimization (quantization, pruning, distillation) — a strong plus.

Proficiency in English

What we offer

Get to know the Team

The Data Science (Geo Vision) team focuses on improving maps and building map-based intelligence, including localization, routing, and traffic forecasting. We use Computer Vision, Information Retrieval, and Large Language Models (LLMs) to process diverse signals like images, text, and GPS probes. We are looking for an engineer who excels at building the scalable software foundations that power these advanced models.

Life at Grab

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 sexual orientation, and other attributes that make each Grabber unique.

What’s it like to work at Grab?

Play video

Data Scientist

Save

Saved

Open sharing options

Share

Quyền lợi

Life at Grab

The role at a glance

The Data Science (Geo Vision) team improves Grab's maps and builds map-based intelligence (localization, routing, travel-time, traffic forecasting) using computer vision and deep learning on images, video, and GPS signals.

As a Data Scientist, you'll focus on bringing computer vision models to embedded/edge platforms for map creation. You will be working onsite and reporting to the Head of Data Science based in Cluj.

What you'll work on

Help adapt and improve CV models (detection, segmentation, tracking) to run on resource-constrained edge devices.

Apply model compression — quantization, pruning, knowledge distillation — to shrink models while preserving accuracy.

Profile on-device performance (latency, memory, power) and help build efficient inference pipelines.

Support training and evaluation, and use AI agents/tooling within the team's quality guidelines.

What you'll gain: hands-on experience taking deep learning models to on-device deployment, plus skills in model optimization and real-time edge performance.

Skills you need

Pursuing or recently completed a degree in Computer Science, Electrical Engineering, or a related field.

Familiarity with Python and some of: PyTorch/TensorFlow, NumPy, OpenCV, and scikit-learn.

Solid ML and deep learning / computer vision fundamentals.

Interest in or exposure to embedded systems, edge deployment, or model optimization (quantization, pruning, distillation) — a strong plus.

Proficiency in English

What we offer

Get to know the Team

The Data Science (Geo Vision) team focuses on improving maps and building map-based intelligence, including localization, routing, and traffic forecasting. We use Computer Vision, Information Retrieval, and Large Language Models (LLMs) to process diverse signals like images, text, and GPS probes. We are looking for an engineer who excels at building the scalable software foundations that power these advanced models.

Life at Grab

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 sexual orientation, and other attributes that make each Grabber unique.

What’s it like to work at Grab?

Play video

Data Scientist

Save

Saved

Open sharing options

Share

Meet the

Data Science team

Our Data Science team is on a mission to create delightful experiences for our users. Every day, they dive into the data to uncover new and intelligent ways to deliver hyperlocal services and solutions to our communities in Southeast Asia.

Every small step of innovation at Grab has an instant impact on hundreds of millions of active users. Nothing is more exciting than facing challenges, exploring uncertainties and advancing the state-of-the-art in artificial intelligence.

“ ”

Jia Chen

Head of Data Science, Integrity

My journey has been fueled by a passion for making a tangible impact through data. Having been a Senior Data Scientist at GrabFin, and now a Lead Data Scientist at Grabads, I found the perfect opportunity to work with massive datasets, which has led to greater impact in my work.

“ ”

Arpit Goel

Lead Data Scientist in GrabAds

I get to bring data to life throughout the product journey – from scoping problems and setting metrics to experimenting and tweaking things for the better. It's not just about numbers; it's about actively shaping and improving our products every day.

“ ”

Ki Fong Pua

Senior Data Scientist (Analytics) at Grab

The Application

Process

What can you expect when you apply for a role at Grab? Here’s what our hiring process looks like.

Step 1: Apply.

We have a range of open roles from Marketing to Engineering and everything in between. Find the one that’s best for you and show us why you’re our next teammate.

Step 2: Getting to know you.

Next, you’ll have a video or phone interview with one of our recruiters to chat about you, the role, and your past work experiences.

Step 3: Testing, testing… 123.

Some roles might require assessments and/or a technical competency interview. For other roles, there might be an additional interview – speak with your recruiter for application details.

Step 4: Is it a culture match?

Finally, we’ll find out how we fit together, if your career vision aligns with our mission, how you embody the 4 H's, and your working style and personality.

Grab a spot in our talent community

Interested in what’s next at Grab? Join our talent community to get early access to opportunities and updates on our teams, work, and culture.

Join now

© Grab 2026

Featured Links

Recruitment Privacy Policy

Cookie Policy

Sitemap

Grab.com

Equal opportunity

Grab is an equal opportunity employer. We owe our success to the talents of our globally-diverse team and the varying perspectives they add to our thriving community.

Recruitment agencies

Grab does not accept unsolicited resumes sent by recruiting agencies. Please do not forward resumes to our job postings, Grab employees or other parts of the business. Grab will not be liable to pay any fees to agencies for candidates hired as a result of unrequested resumes.

Social Links

We care about your privacy

Thank you, your preferences have been updated.

By clicking "Accept All", you agree to the storing of cookies on your device to give you the most optimal experience using our website. We may also use cookies to enhance performance, analyse site usage and to personalise your experience.

Manage Preferences

Accept All

Essential Only