Head of AI Engineer (Vietnam)

As the Head of AI Engineer at Bjak, your responsibilities span from leading a team of AI engineers to collaborating on defining project objectives. You'll be designing, developing, and implementing AI models to solve intricate business challenges, ensuring that the entire model lifecycle is managed efficiently. Staying updated on AI advancements and driving data-driven decision-making are also crucial aspects of your role.

To qualify for the Head of AI Engineer role at Bjak, you must be a Vietnamese citizen or permanent resident with a Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or a related field. Proven experience leading AI projects, proficiency in AI frameworks and programming languages like Python, and strong problem-solving and leadership skills are also essential.

Yes, the Head of AI Engineer position at Bjak is fully remote, allowing you to work from anywhere in Vietnam. This flexibility enables you to contribute to exciting projects while balancing your personal and professional life.

At Bjak, we are committed to your career growth as the Head of AI Engineer. You'll have access to strong learning and development plans, ensuring you stay at the forefront of AI and machine learning advancements, alongside opportunities for promotions and role expansion as Bjak continues to grow.

Bjak promotes a collaborative work culture, emphasizing teamwork and innovation. As the Head of AI Engineer, you'll thrive in an international environment filled with diverse talents, where creative problem-solving and cutting-edge ideas are celebrated and encouraged.

When answering this question, illustrate a specific AI project where you played a crucial role. Detail your responsibilities, the technologies you used, and the project's impact on the organization. Highlight your leadership skills and the collaborative effort with team members.

Discuss the various methods you use to keep your knowledge current, such as following relevant publications, attending industry conferences, or engaging with online communities. Emphasize your passion for continuous learning in AI and how you apply this knowledge in your work.

Talk about your mentoring philosophy, which might include regular one-on-one meetings, providing constructive feedback, and encouraging self-directed learning. Share examples of how you've successfully guided team members in the past.

Provide insights into your practical experience in deploying AI models. Discuss any challenges you faced, how you overcame them, and emphasize the importance of monitoring model performance post-deployment.

List the AI tools and frameworks you are familiar with, such as TensorFlow, PyTorch, or scikit-learn. Discuss how you have leveraged these tools in your past projects to deliver successful outcomes.

Explain your approach to conflict resolution, emphasizing open communication and creating an environment where team members feel safe to express their opinions. Share examples of how you've successfully resolved disputes.

Detail your experience with data preprocessing steps, including cleaning, normalizing, and feature selection. Highlight how these processes have improved model performance in your previous projects.

Choose a specific example where you encountered a significant challenge in AI engineering. Discuss the situation, your thought process, the actions you took, and the outcome. This shows your problem-solving abilities.

Discuss your strategies for developing scalable AI solutions, such as modular design, choosing the right infrastructure, and planning for data growth. Share relevant experiences where scalability was achieved successfully.

Talk about your passion for AI technologies and innovations. Mention specific areas of AI that particularly interest you and how you see yourself making a positive impact through your work in this field.