Machine Learning Leader

This is a leadership role that requires a strong understanding of AI and machine learning concepts. The ideal candidate will have experience in leading/managing AI/ML projects, achieving clear & measurable business objectives.

• Technical Leadership: Provide technical leadership and strategic direction for the AI team, aligning with overall company objectives.
• Team Management: Lead and mentor a team of data engineers, MLOps engineers, and machine learning engineers to achieve project objectives and deliverables (development and deployment of ML models for AI use cases across the platform).
• Architecture Design: Contribute to AI/ML architecture design and implementation.
• Collaboration: Collaborate with business, engineering, infrastructure, and data science teams to translate their needs or challenges into production-grade Artificial Intelligence and Machine Learning models for batch and real-time requirements.
• Communication: Serve as a primary point of contact for US & Thryve leaders, ensuring clear communication and aligning with project goals and objectives.
• Guidance: Guide the AI/ML engineers with respect to business objectives, connecting the dots, and helping the team come up with optimal ML models based on use cases.
• Operations: Manage day-to-day operations, ensuring adherence to process, scope, quality, and timelines.
• Engagement Coordination: Assume the role of an engagement coordinator between the Thryve India team and US counterparts (techno-functional).
• Risk Management: Highlight risks and concerns to the leadership team and work with multiple stakeholders to establish alignment, contingency, and/or mitigation plans as required.
• Delivery Tracking: Proactively track delivery statuses and project progress, taking ownership of all deliverables from Thryve.
• Stakeholder Communication: Communicate effectively with team members, US stakeholders, and management.
• Professional Development: Stay up-to-date with the latest trends and advancements in AI and ML, and identify opportunities for the team to implement new models and technologies.
• Process Improvement: Propose and implement best engineering and research practices for scaling ML-powered features, enabling fast iteration and efficient experimentation with novel features.

• Bachelor's degree in engineering, computer science, or a related field.
• 12 to 15 years of total experience, with at least 2 years of experience leading/managing AI/ML projects, achieving clear & measurable business objectives.
• Strong understanding of US Health insurance with at least 3+ years of experience in the same.
• Experience and understanding of the entire MLOps pipeline, from data ingestion to production.
• Strong understanding of AI/ML concepts & algorithms, including supervised, unsupervised, and reinforcement learning, as well as MLOps.
• Proven ability to take successful, complex ideas from experimentation to production.
• Hands-on experience with Google Cloud Platform (GCP) or any public cloud platform.
• Excellent communication, presentation, and interpersonal skills.
• Proven experience in leading, motivating & inspiring teams to foster collaboration.
• Proficient in identifying, assessing, and calling out risks and mitigation plans to stakeholders.
• Experience in implementing process improvements and learning from past projects to enhance future performance.
• Ability to analyze external and internal processes and create strategies for service delivery optimization.
• Experience in working with diverse teams and stakeholders, understanding their needs and managing expectations.