1 day ago
Singapore, SingaporeStaff+
Responsibilities
- Drive ML strategy and technical direction across the organization.
- Design and develop end-to-end machine learning systems covering data pipelines, model training, evaluation, and deployment.
- Lead experimentation and A/B testing frameworks to measure and optimize model performance.
- Build scalable classifiers and ML tools using deep learning, data regression, and rules-based models.
- Adapt and optimize ML methods for distributed clusters, multicore SMP, and GPU environments.
- Translate cutting-edge ML research into production systems in partnership with research teams.
- Mentor and influence ML engineers and establish strong ML engineering practices.
- Identify ML opportunities and influence staffing and prioritization of initiatives.
- Communicate complex ML systems and architectural decisions to technical and non-technical stakeholders.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- 12+ years of experience with programming languages such as Python, C++, or Java.
- 8+ years of experience in machine learning, recommendation systems, pattern recognition, data mining, or deep-learning-based methods.
- Experience leading projects with industry-wide impact and driving large cross-functional engineering efforts.
- Experience influencing technical direction through design reviews, proposals, or architectural decisions.
- Experience planning multi-year roadmaps and aligning short-term projects with long-term missions.
- Experience communicating and working across functions to drive solutions.
- Preferred experience applying ML models to revenue or user-facing products at scale.
- Preferred expertise in ranking, relevance, personalization, recommender systems, deep learning frameworks, ML infrastructure, and large-scale model training pipelines.
- Preferred familiarity with responsible AI practices, MLOps, model monitoring, production ML systems, AI skill development, and ML research contributions.
Categories
About Meta
Meta builds social platforms and communication apps—including Facebook, Instagram, WhatsApp, and Messenger—and develops AR/VR hardware and software such as Quest to power immersive computing. It monetizes primarily through advertising tools for businesses, with additional revenue from devices and services, and operates a massive global infrastructure. Founded in 2004 and headquartered in Menlo Park, California, Meta Platforms, Inc. is a public company traded on Nasdaq under the ticker META.