Machine Learning Engineer

Skill: Design and Development of Machine Learning Models

1. Can you describe a project where you designed and developed a machine learning model from scratch?
2. What factors do you consider when designing a machine learning model?
3. What is your process for developing machine learning models?
4. How do you ensure the efficiency of your machine learning models?
5. What is your approach to handling overfitting in machine learning models?

Skill: Project Ownership

1. Can you describe a project that you owned from conception to deployment?
2. How do you ensure that a project meets business requirements?
3. What is your approach to maintaining momentum on a project?
4. How do you handle changes in project requirements?
5. What is your approach to project documentation?

Skill: Collaboration with Developers, Data Engineers, and Business Stakeholders

1. Can you describe a project where you collaborated with developers and data engineers?
2. How do you approach gathering requirements from stakeholders?
3. What is your experience with cross-functional team collaboration?
4. How do you handle disagreements in a team?
5. What is your approach to stakeholder communication?

Skill: Evaluation and Selection of Machine Learning Techniques

1. Can you describe a project where you had to evaluate and select a machine learning technique?
2. What factors do you consider when selecting a machine learning technique?
3. What is your experience with supervised learning techniques?
4. How do you validate the effectiveness of your selected technique?
5. What is your approach to feature selection in machine learning?

Skill: Deployment of Machine Learning Models in AWS

1. Can you describe a project where you deployed a machine learning model in AWS?
2. What is your experience with AWS architecture design?
3. What is your experience with AWS best practices?
4. How do you ensure the security of your AWS deployments?
5. What is your approach to cost management in AWS?

Additional Notes

1. Ensure to assess the candidate's communication skills and their ability to explain complex concepts in a simple manner.
2. Look for examples of problem-solving and critical thinking in the candidate's responses.
3. Assess the candidate's ability to work in a team and handle conflicts.
4. Look for examples of the candidate's ability to manage projects and meet deadlines.
5. Assess the candidate's knowledge of AWS and their experience with deploying machine learning models in a large-scale environment.