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Grab

Senior Machine Learning Engineer (ACE)

Grab is hiring a Senior Machine Learning Engineer (ACE). Level rates it ; you can apply on Grab.

Level's read on this job

  • On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
  • The posting mentions ChatGPT, PyTorch and TensorFlow among its tools and skills.
  • Level classes it as a senior role.
  • Grab has 436 other open roles on Level.

AI in this role

chatgptpytorchtensorflow

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

Get to Know the Team

In the ACE (Online Deliveries, Omni-commerce) Data Science team, you are at the core of Grab's largest business pillars. We build and deploy AI/ML models to power seamless user experiences across the food ecosystem — from instant deliveries to restaurant reservations. Our mission is to enhance user satisfaction and platform efficiency by solving unique challenges in geospatial demand, proactive reliability, and transformative AI-driven discovery.

You will report to our Senior Data Science Manager and based onsite in our office in Petaling Jaya, Selangor.

Get to Know the Role

As a Senior Machine Learning Engineer, you will lead the development of intelligent systems that shape how millions of users interact with Grab. You will move beyond basic forecasting to build proactive, "self-healing" reliability systems and leverage Generative AI to redefine the user experience.

The Critical Tasks You Will Perform

You will be working on machine learning engineering projects on one or a few areas below:

  • Strategic Demand Shaping: Architect solutions that steer demand toward higher serviceability. You will design spatial and temporal nudges — such as shifting users from on-demand to scheduled delivery models or redirecting orders from supply-constrained to under-utilized merchants — to maximize network throughput and balance platform capacity in real time.
  • Grab Content Enrichment: Transform "thin" or unstructured data into rich, machine-readable metadata. You will build systems that power new in-app discoveries and serve external AI demands (e.g., ChatGPT or Google's AI search).
  • Demand Generation & Growth: Identify "hidden" customer patterns across food and dining to unlock new demand for ACE.
  • Reliability & Dispute Arbitration: Predict friction before it happens. You will develop models to identify order risks and cancellation probabilities, automating "who is at fault" logic and facilitating proactive interventions to maintain platform trust.
  • Transformative GAI Experience: Lead the integration of Generative AI (GAI) to fundamentally evolve the current user journey and interface.

Your key responsibilities are:

  • Extract Insights: Analyze massive datasets (transactional, behavioral, and geospatial) to decode food ordering patterns and optimize the end-to-end journey for food ordering journey.
  • Build, Iterate, and Deploy: Own the end-to-end lifecycle of ML models, translating tens of millions of eaters interactions into production-grade solutions through rigorous A/B testing and monitoring.
  • Cross-Function Collaboration: Partner with product managers, engineers, analytics, design and operations teams to scale solutions.
  • Innovation: Contribute to team's innovation and IP creation

What Essential Skills You Will Need

  • Education: Bachelor's Degree with 4+ years of relevant experience in Machine Learning, Statistics, Computer Science, Economics, or Operations Research.
  • Technical Depth: Deep understanding of ML/DL foundations, optimization algorithms, and data mining. Proficiency in frameworks like TensorFlow or PyTorch. Proven experience in the application of Large Language Models
  • Programming: Strong proficiency in Python or Scala.
  • Problem Solving: Translate complex business problems (like multi-party dispute arbitration or spatial demand shaping) into scalable math/code solutions.
  • Soft Skills: Motivated to learn and is able communicate by articulating technical insights to non-technical stakeholders.

 

Life at Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

  • We have your back with Term Life Insurance and comprehensive Medical Insurance.
  • With GrabFlex, create a benefits package that suits your needs and aspirations.
  • Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
  • We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
  • Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For At Grab

We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

How we rate this

Senior Machine Learning Engineer (ACE) at Grab rates 88 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ChatGPTPyTorchTensorFlow

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$200k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. What's a project where you used ChatGPT hands-on?
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. What are the limits of TensorFlow that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: ChatGPT, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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