Lead Machine Learning Engineer (Fulfilment)

Company Description

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.

Job Description

Get to know the Team

The Fulfilment Tech family is one of the pillars that enable Grab to out-serve our consumers and partners in various businesses and marketplaces across Southeast Asia. We are developing high-throughput, real-time distributed systems that use sophisticated machine learning techniques to handle hundreds of millions of requests per day. Our mission is to provide the best-in-class products and experiences to our driver partners, improve driver partner opportunities and efficiency to fulfil consumer 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 consumers.

At the Fulfilment machine engineering team, we are working to solve challenging problems in the marketplace that involve dynamic pricing and supply and demand management. We're looking for a Lead Machine Learning Engineer to join our team and help bring that vision to life by developing and refining cutting-edge reinforcement learning models and simulation platforms.

Get to know the Role

This is a hands-on role focused on building large-scale simulation platforms. You'll be reporting to the Senior Engineering Manager and work onsite at Grab One North Singapore office. You'll help create a digital twin of Grab's dynamic marketplace, which encompasses tens of thousands of consumers, drivers, and merchants. Furthermore, you'll design and implement reinforcement learning, optimization, and control models to address critical business challenges within Grab's marketplace and deploy these solutions at scale.

You have understanding of the software development lifecycle and engineering best practices, along with significant experience developing production-ready Machine Learning systems. Additionally, experience with regression, classification, and optimization problems, applying reinforcement learning (or control theory), and working with real-time streaming data is essential.

The Critical Tasks You Will Perform

• Develop and architect a simulation platform to model the real-world marketplace behaviour across Grab's diverse service offerings.
• Define and drive the technical roadmap for integrating the Simulation Platform into the product development lifecycle within the Fulfilment Tech Family
• Design the Simulation Platform to allow comprehensive "What-If" scenario analysis, facilitating data-driven product decisions.
• Collaborate with data scientists and engineers to design simulation workflows that support platform policy designs and optimizations.
• Work with data scientists and engineers to create Simulation SDKs that enhance the user experience of the platform.
• Partner with Data Scientists to integrate and build feedback loops, allowing optimal policy search using the simulation platform.
• Design and scale the simulation platform to execute hundreds to thousands of simulations daily.
• Identify and resolve performance bottlenecks and debug simulation divergence issues.
• Conduct service capacity and demand planning, software performance analysis, costing, tuning, and optimization.
• Participate in code and design reviews to uphold high development standards.

Qualifications

What Essential Skills You Will Need

You have :

Additional Information

Life at Grab

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

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.

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