Lead Edge AI Engineer

Lead Edge AI Engineer

• Team Data Science
• Location Cluj-Napoca, Romania
• Job Type Full-time

The role at a glance

Get to know the Team

The Data Science (Geo Vision) team at Grab focuses on improving the maps and building map-based intelligence such as localization, routing, travel time estimation, and traffic forecasting. We use Computer Vision and conventional machine learning methods on a variety of signals—specifically utilizing edge device footage—to understand our locations and road networks.

Get to know the Role

We are looking for a Lead Data Scientist / Edge AI Engineer to lead edge development for our edge devices. A key focus will be Multi-Task & Action Recognition Development, where the successful candidate will be responsible for developing and refining multi-task learning models and video action recognition systems for our edge devices.

You will work onsite and will report to the Head of Data Science based in the Cluj Office.

The Critical Tasks You Will Perform

• Multi-Task & Action Recognition Development: Develop and refine multi-task learning models (specifically Hydranet architecture) and video action recognition systems using PyTorch.
• Edge Deployment & Engineering: Deploy Computer Vision algorithms into embedded Android platforms, utilizing the Qualcomm SNPE / QNN SDK to interact directly with the DSP.
• Resource Efficiency: Conduct rigorous performance analysis to reduce power consumption and manage thermal constraints. You will ensure model switching latency remains minimal to maintain recording integrity.
• System Stability: Implement safety mechanisms to ensure system stability during dynamic model graph reconfiguration.
• Collaboration: Collaborate with Firmware and Mobile teams to integrate signals for model decision-making.

Read more Skills you need

What Skills you will Need:

• Educational Background: Bachelor's degree or higher in Computer Science, Electrical Engineering, or a related field.
• Experience: Minimum of 5 years of experience in computer vision and machine learning, with a mandatory focus on Edge AI deployment and optimization.
• Mandatory Frameworks: Deep expertise in PyTorch. You must be proficient in Video Action Recognition and Learning network design.
• Edge Constraints: Deep understanding of resource-constrained environments (memory bandwidth, thermal management and power consumption).
• Optimization: Knowledge of general model optimization techniques for edge devices (quantization, pruning, graph splitting).
• Communication: Proficiency in English (speaking and writing) with the ability to present technical data insights.

The Nice-to-Haves:

• Context-Aware DSP Optimization & Dynamic Graph Execution: Experience designing and implementing intelligent runtime management logic (dynamic model switching or conditional computation) on Android to dynamically load/unload specific heads of multi-task architectures (e.g., Hydranet) on the Qualcomm Hexagon DSP.
• DSP & SNPE Expertise: Proven experience with Qualcomm DSP (Hexagon), SNPE (Snapdragon Neural Processing Engine), or QNN SDK.
• Android Development: Background in Android development for edge devices, particularly in handling hardware-software interactions and resource utilization.
• Sensor Fusion: Experience with camera localization and motion estimation using a combination of GPS, IMU, video, and magnetometer.
• Core CV Skills: Experience with advanced computer vision techniques, including camera localization, motion estimation, and 3D reconstruction.
• System-Level Software: Proficiency in low-level system software and hardware-software interactions on Qualcomm chipsets.

Read more What we offer

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 create economic empowerment for the people of Southeast Asia.

Read more 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.

Benefits at Grab:

• Insurance: Comprehensive Term Life Insurance and Medical Insurance.
• Customized Benefits: GrabFlex offers a tailored benefits package.
• Parental Leave: Maternity and Paternity Leave for new parents.
• Support Programs: Confidential Grabber Assistance Programme for life's challenges.
• Well-being Initiatives: Access to Wellbeing@Grab, including health programs, webinars, and events.
• Work-Life Balance: FlexWork arrangements to support personal and professional life.

Read more

What’s it like to work at Grab?

Play video

Lead Edge AI Engineer

Apply Now Share

View our location

Our teams in Romania are always on the lookout to boost their knowledge and drive innovation to power our products. Learn more about our Research & Development (R&D) Centre where we fuel innovation.

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 ChenHead 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 GoelLead 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 PuaSenior 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

Want to be the first to know about Grab opportunities? Keen to stay up-to-date with our latest revelations? Ready to learn more about life at Grab and our amazing teams?

Join our talent community and you’ll never miss a beat.

Join now