Deskripsi Pekerjaan
Are you passionate about shaping the future of AI-driven commerce? ByteDance is seeking a visionary Tech Lead for Machine Learning to join our Global E-Commerce team in Singapore. In this role, you will lead the architecture and development of our next-generation conversational AI agent system. Our mission is to build a unified, intelligent agent capable of learning from global interactions to provide seamless, human-like shopping experiences at scale.
As a Tech Lead, you will bridge the gap between cutting-edge research and production-grade engineering. You will lead a high-performing team of ML engineers to solve complex challenges in Natural Language Processing (NLP), Large Language Models (LLMs), and Reinforcement Learning. If you thrive in a fast-paced environment and are excited about building platforms that impact millions of users globally, we want to hear from you.
Tanggung Jawab
- Lead the design, development, and deployment of scalable Conversational AI agents within the E-commerce ecosystem.
- Architect robust ML pipelines that handle high-concurrency request patterns and real-time inference.
- Mentor a team of Machine Learning Engineers, fostering a culture of technical excellence, code quality, and innovation.
- Collaborate with product managers and cross-functional teams to define the roadmap for intelligent agent features.
- Optimize LLM performance, latency, and cost-efficiency to ensure a premium user experience.
- Drive research initiatives to integrate multi-modal data and contextual memory into our agent architecture.
- Establish best practices for model evaluation, monitoring, and A/B testing in production environments.
Kualifikasi
- Master’s or PhD degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of industry experience in Machine Learning, with a strong focus on NLP or Generative AI.
- Demonstrated experience leading technical teams and driving complex, multi-quarter engineering projects.
- Proven expertise in building and deploying LLMs or transformer-based architectures at scale.
- Proficiency in deep learning frameworks such as PyTorch or TensorFlow, and distributed training techniques.
- Strong software engineering skills in Python, C++, or Go, with a deep understanding of system design.
- Experience with large-scale data processing frameworks like Spark or Flink is a plus.
- Excellent communication skills, with the ability to articulate technical concepts to non-technical stakeholders.