at Grab
Full TimeLife 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 ML Platform team at Grab empowers teams across the company to harness the power of machine learning. We're building cutting-edge tools and infrastructure that democratize AI, driving innovation throughout Grab's services.
Get to Know the Role:
As our Senior Machine Learning Engineering Manager, you'll lead the evolution of Grab's ML Platform. This is a high-impact role where you'll shape the way machine learning drives value across our organization.
The Day-to-Day Activities:
Lead and Inspire: Build and mentor a high-performing team of platform and machine learning engineers, creating a collaborative and innovative environment.
Architect the Future: Define the strategic vision for Grab's ML Platform, aligning it with our core business objectives for maximum impact.
Build for Efficiency: Design and implement tools that streamline the entire ML workflow, enabling rapid development and deployment of impactful ML solutions.
Champion Scalability: Collaborate with stakeholders to ensure our ML Platform scales seamlessly, empowering data scientists and engineers company-wide.
Drive Technical Excellence: Foster a culture of quality through code reviews, design discussions, and best-practice implementation.
Attract and Develop: Actively contribute to our talent acquisition strategy and shape initiatives that support the growth of our team.
The Must-Haves:
Proven Experience: 6+ years of relevant experience in machine learning engineering or similar roles, including at least 2 years of demonstrated success in a management position.
Technical Mastery: Deep expertise in building and deploying ML platforms, including a strong command of programming languages (Python, R, or Java), cloud platforms (AWS, Azure), and containerization (Kubernetes).
MLOps: In-depth knowledge of MLOps principles, enabling the productionalization of ML models (training, validation, deployment, monitoring).
Strategic Visionary: Ability to translate business needs into a technical roadmap, ensuring our ML Platform consistently creates value.
Exceptional Leader: Possess communication and mentorship skills that inspire teams and attract top talent.
Our Commitment
We recognize that with these individual attributes come different workplace challenges, and we will work with Grabbers to address them in our journey towards creating inclusion at Grab for all Grabbers.
