Lead Machine Learning Engineer – Generative AI

As a Lead Machine Learning Engineer – Generative AI at Cosuno, you will lead the development of AI solutions that transform construction industry processes into intelligent workflows. You’ll architect and implement machine learning models, customize large language models for specific challenges, conduct experiments to validate effectiveness, and collaborate with engineering and product teams for production initiatives.

To apply for the Lead Machine Learning Engineer – Generative AI position at Cosuno, you need a master’s or PhD in Computer Science, Mathematics, or a related field. Furthermore, strong Python programming skills, experience with ML ops, and a deep understanding of machine learning fundamentals and neural network architectures are essential.

Cosuno fosters an environment for professional growth by encouraging mentorship, an open feedback culture with regular one-on-ones, and opportunities to collaborate with skilled professionals. You’ll have the chance to share your expertise and help shape the next generation of AI solutions.

In the role of Lead Machine Learning Engineer – Generative AI at Cosuno, you will work with advanced AI frameworks such as PyTorch or TensorFlow. Your expertise in Python and ML ops will help guide you as you deploy cutting-edge models to productions.

The work culture at Cosuno for a Lead Machine Learning Engineer – Generative AI is open-minded and collaborative. You can work fully remotely with flexible hours, participate in company off-sites, and enjoy a dynamic international team environment that focuses on results and innovation.

Discuss your specific experiences with various machine learning models, including how you selected them based on the project requirements. Highlight real-life applications where you successfully utilized these models, and explain the impact they had on the overall project.

Use the STAR method to structure your response: Situation, Task, Action, and Result. Describe the specific problem and your methodology for addressing it, including any unique solutions you implemented, and focus on the positive outcomes.

Explain your method for customizing large language models, including the importance of understanding specific industry needs. Mention any tools or frameworks you use and the importance of iterative testing and feedback in your process.

Share your insights on important best practices such as continuous integration and deployment (CI/CD), version control for models, monitoring model performance post-deployment, and collaborating with cross-functional teams to ensure seamless integration.

Articulate how you have applied neural networks in past projects, discussing the types of networks used and reasons for choosing them. If applicable, mention the results achieved with their implementation, demonstrating your understanding of their capabilities.

Discuss strategies you employ when designing AI solutions, including scalability considerations and the importance of conducting robust validation experiments. Highlight your experience with performance metrics and monitoring.

Describe your approach to mentorship—whether through one-on-one sessions, workshops, or code reviews. Highlight success stories of how your guidance has helped team members advance their skills.

Share your sources for staying updated, such as attending conferences, participating in online courses, following key researchers in the field, or engaging with the machine learning community on forums or social media.

Provide an example of how you effectively communicated technical concepts to non-technical stakeholders, emphasizing your ability to tailor your explanations to their level of understanding and the importance of clear communication in project success.

Express your enthusiasm for the role and the potential impact of AI solutions in the construction industry. Discuss how the innovative projects at Cosuno resonate with your career goals and values.