Head of AI Engineering, United States

As the Head of AI Engineering at BJAK, your responsibilities include leading and mentoring a talented team of AI engineers, defining project objectives together with product managers, designing and developing AI models, and overseeing the entire AI model lifecycle from data collection to deployment. You'll also be expected to incorporate the latest AI advancements and best practices to deliver innovative solutions.

To qualify for the Head of AI Engineering role at BJAK, candidates should hold a Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or a related field. A proven track record in leading successful AI projects, proficiency in relevant programming languages like Python, and strong expertise in data preprocessing and machine learning frameworks are also essential.

BJAK promotes an environment conducive to professional growth for the Head of AI Engineering through attractive remuneration, performance incentives, and strong learning and development plans. Our flat organizational structure encourages ownership and initiative, allowing you to earn leadership opportunities by consistently delivering outstanding results.

The Head of AI Engineering at BJAK can expect a dynamic and fast-moving work environment. With a flat organizational structure, you’ll find a culture that fosters collaboration and innovation, where each team member's contributions are valued, and cross-functional engagement is encouraged.

Essential skills for the Head of AI Engineering at BJAK include strong leadership abilities, excellent problem-solving skills, proficiency in AI and machine learning frameworks, effective communication skills, and a passion for staying at the forefront of AI advancements. Critical thinking and team management capabilities are also key to thriving in this role.

In your response, share specific examples of AI projects you’ve led, focusing on your role in team guidance, project planning, and overcoming challenges. Highlight the successful outcomes and any innovative solutions you implemented.

Discuss your mentoring style, emphasizing personalized support and constructive feedback. Share any methodologies you’ve successfully used to foster growth and development in junior team members.

Illustrate your commitment to continuous learning by mentioning specific sources such as conferences, academic journals, websites, or online courses. It can also be helpful to mention networks or communities where you engage with other AI professionals.

Detail your process for deploying AI models, including steps like validation and real-world testing. Highlight any challenges you've faced and how you ensured the deployment was successful and efficient.

List specific tools and frameworks you are proficient in, such as TensorFlow, PyTorch, or scikit-learn. Explain how you've applied these technologies to solve problems in past projects.

Talk about your organizational strategies, such as using project management tools, setting clear deadlines, and regular check-ins with your team to ensure alignment and progress.

Provide a detailed example of an AI challenge, discussing the technical difficulties you faced, how you approached the problem, the solutions you considered, and the ultimate resolution.

Discuss your hands-on experience with data preprocessing techniques and feature engineering methodologies. Share any examples where this work significantly impacted the performance of an AI model.

Outline your approach to building secure and scalable AI systems, focusing on practices like code reviews, testing protocols, and utilizing cloud services when applicable.

Share your passion for AI and how BJAK’s mission resonates with you. Discuss the opportunities for innovation and impact you see in shaping intelligent task automation to improve lives globally.