Machine Learning Engineering Manager, AI-powered Conversational Search

Team Leadership:

• Recruit, hire, and mentor a high-performing team of machine learning engineers and data scientists.
• Foster a collaborative and inclusive team culture, promoting knowledge sharing and continuous learning.
• Set clear goals, provide regular feedback, and promote professional growth and development of team members.

Project Management:

• Develop and manage project plans, timelines, and budgets for machine learning initiatives.
• Ensure the successful execution of projects, from ideation and prototyping to production deployment.
• Collaborate with cross-functional teams to define project requirements and priorities.

Technical Leadership:

• Drive the technical vision and strategy for the Machine Learning Team.
• Oversee the research, development, and deployment of machine learning models and algorithms.
• Stay current with the latest advancements in the field and ensure that our projects leverage cutting-edge technologies.

Quality and Performance:

• Implement best practices for model development, data pipelines, and model evaluation.
• Monitor and optimize the performance, scalability, and reliability of machine learning systems.
• Ensure that our AI solutions meet high standards of accuracy and efficiency.

Stakeholder Communication:

• Collaborate with leadership, product managers, customer success staff, and other teams to align machine learning initiatives with business goals.
• Provide regular updates and reports on project status, challenges, and successes to stakeholders.

• Master's degree in Computer Science, Machine Learning or a related field. A Ph.D. is a plus.
• 5+ years industry experience
• Proven experience in leading or managing machine learning/AI teams, with a track record of successful project delivery.
• Proficiency in programming languages such as Python and experience with relevant libraries (e.g., TensorFlow, PyTorch).
• Excellent problem-solving and analytical skills.
• Strong communication skills.
• Knowledge of software engineering best practices and experience with deploying machine learning models in production environments.