Applied AI Scientist

Full-time • Bangkok

Job Description

We are seeking a talented Applied AI Scientist to join our team and contribute to the development of cutting-edge AI solutions. As an Applied AI Scientist, you will work on interdisciplinary projects to solve complex problems across various domains using advanced machine learning and deep learning techniques. You will collaborate with cross-functional teams to understand business requirements, design experiments, develop models, and deploy AI solutions in real-world environments.

Responsibilities

Develop and implement cutting-edge machine learning algorithms and techniques to solve complex problems in various domains.
Collaborate with cross-functional teams to understand business requirements and develop AI solutions that address specific needs.
Conduct research to stay updated with the latest advancements in AI and identify opportunities to apply them to existing projects.
Design experiments, collect and analyze data, and iterate on models to improve performance and accuracy.
Evaluate the feasibility and potential impact of AI solutions, and communicate findings to stakeholders.
Provide technical guidance and mentorship to junior team members.

Requirements

Advanced degree (Ph.D. preferred) in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Strong background in machine learning, deep learning, and statistical modeling, with hands-on experience in applying these techniques to real-world problems.
Proficiency in programming languages such as Python, R, or Java, and experience with libraries/frameworks like TensorFlow, PyTorch, or scikit-learn.
Experience with big data technologies and platforms (e.g., Hadoop, Spark) for handling large-scale datasets.
Excellent problem-solving skills and ability to work independently as well as part of a team.
Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.

Preferred Qualifications:

Experience with natural language processing (NLP), computer vision, or other specialized areas of AI.
Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models in production environments.
Familiarity with agile development methodologies and tools for version control and collaboration (e.g., Git, Jira).
Publications in top-tier conferences or journals related to artificial intelligence and machine learning.