job description
Join ASUS AICS as an AI Engineering & LLM Systems Manager and lead a cutting-edge Machine Learning Engineering team in developing production-ready Large Language Model (LLM) applications and advanced AI systems. Based in the vibrant tech hubs of Bali (Canggu, Ubud, Denpasar, and more), you’ll drive innovation in AI-driven solutions, scaling high-performance models for real-world impact.
This is a unique opportunity to shape the future of AI at a global technology leader, working with cross-functional teams to deliver next-generation AI products. If you’re passionate about LLM optimization, MLOps, and AI infrastructure, and thrive in a dynamic, collaborative environment, we want to hear from you.
Responsibility
- Lead and mentor a high-performing Machine Learning Engineering team focused on LLM and AI system development.
- Design, implement, and optimize scalable AI/ML pipelines for production-grade LLM applications.
- Collaborate with research and product teams to translate AI models into real-world, user-facing solutions.
- Drive MLOps best practices, including model deployment, monitoring, and continuous improvement.
- Oversee AI infrastructure (GPU/TPU clusters, distributed training) to ensure high performance and cost efficiency.
- Stay ahead of emerging AI trends (e.g., fine-tuning, RLHF, retrieval-augmented generation) and integrate them into ASUS products.
- Ensure compliance with data privacy, security, and ethical AI standards in all deployments.
- Partner with stakeholders to align AI initiatives with business goals and market needs.
Qualifications
- 5+ years of experience in AI/ML engineering, with at least 2 years in a leadership role.
- Proven expertise in LLM development (e.g., fine-tuning, prompt engineering, inference optimization).
- Strong background in Python, PyTorch/TensorFlow, and distributed computing frameworks (e.g., Ray, Horovod).
- Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools (MLflow, Kubeflow, SageMaker).
- Deep understanding of AI infrastructure (GPU clusters, containerization, Kubernetes).
- Familiarity with NLP, generative AI, and retrieval systems (e.g., vector databases, RAG pipelines).
- Excellent problem-solving and communication skills to bridge technical and business teams.
- Bachelor’s/Master’s/PhD in Computer Science, AI, or a related field (or equivalent experience).