job description
Join MaiStorage as a Senior AI Research Engineer and lead the charge in transforming groundbreaking AI research into scalable, high-performance systems. Based in the vibrant tech hub of Bali, Indonesia, you’ll work at the intersection of machine learning, deep learning, and system optimization, driving innovation in AI-driven solutions for next-generation storage and data processing.
This is a unique opportunity for a passionate AI specialist to collaborate with cross-functional teams, pushing the boundaries of what’s possible in algorithmic efficiency, model deployment, and real-world AI applications. If you thrive in a dynamic, research-focused environment and want to shape the future of AI in enterprise technology, this role is for you.
MaiStorage offers a competitive salary (IDR 20M–28M/month), a culture of innovation, and the chance to work on projects with global impact—all while enjoying Bali’s unparalleled work-life balance.
Responsibility
- Design, develop, and optimize cutting-edge AI/ML models for large-scale data processing and storage systems.
- Bridge the gap between theoretical research and practical implementation, ensuring algorithms are production-ready and scalable.
- Collaborate with data scientists, software engineers, and product teams to integrate AI solutions into MaiStorage’s core infrastructure.
- Research and implement advanced techniques in deep learning, NLP, computer vision, or reinforcement learning as applicable to storage optimization.
- Optimize AI models for performance, latency, and cost-efficiency in cloud or on-premise environments.
- Stay ahead of emerging AI trends and evaluate new tools/frameworks (e.g., PyTorch, TensorFlow, JAX) for adoption.
- Develop custom loss functions, neural architectures, and training pipelines tailored to unique business challenges.
- Document research findings, create technical reports, and present insights to stakeholders.
Qualifications
- Master’s or PhD in Computer Science, AI, Machine Learning, or a related field (or equivalent industry experience).
- Proven experience (3+ years) in AI research, algorithm development, or applied ML engineering in a production environment.
- Expertise in Python, PyTorch/TensorFlow, and ML libraries (e.g., scikit-learn, Hugging Face).
- Strong background in mathematics/statistics (linear algebra, probability, optimization) and distributed computing.
- Experience with large-scale data pipelines, GPU acceleration (CUDA), or MLOps tools (e.g., MLflow, Kubeflow).
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Publications, patents, or open-source contributions in AI/ML are a strong plus.
- Excellent problem-solving skills and ability to communicate complex technical concepts clearly.