AIML Delivery Manager

AIML Delivery Manager

About Thryve Digital Health LLP:

Thryve Digital Health LLP is an emerging global healthcare partner delivering strategic innovation, expertise, and flexibility to its healthcare partners. As a US healthcare conglomerate captive, we have direct access to deep insights that accelerate learning and keep us ahead of the curve. Thryve delivers next-generation solutions that enable our healthcare partners to provide positive experiences to their consumers.

Our global collaborative of healthcare, operations, and IT experts creates innovative and sustainable processes for our clients, engaging ever-evolving consumers and managing the future of healthcare. We value our people and their diverse talents. Thryve is an equal opportunity employer, valuing integrity, diversity, and inclusion. We do not discriminate based on any protected attribute. For more information, please visit www.thryvedigital.com

Role Summary:

The AI Manager leads the AI team, contributing to technical strategy and decision-making. This role involves managing the day-to-day delivery of the AI/ML team, responsible for building, deploying, and maintaining robust, scalable, and efficient ML models.

Essential Responsibilities:

• Provide technical leadership and strategic direction for the AI team, aligning with overall company objectives.
• 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).
• Contribute to AI/ML architecture design and implementation.
• 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.
• Serve as a primary point of contact for US & Thryve leaders, ensuring clear communication and aligning with project goals and objectives.
• 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.
• Manage day-to-day operations, ensuring adherence to process, scope, quality, and timelines.
• Assume the role of an engagement coordinator between the Thryve India team and US counterparts (techno-functional).
• Highlight risks and concerns to the leadership team and work with multiple stakeholders to establish alignment, contingency, and/or mitigation plans as required.
• Proactively track delivery statuses and project progress, taking ownership of all deliverables from Thryve.
• Communicate effectively with team members, US stakeholders, and management.
• 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.
• Propose and implement best engineering and research practices for scaling ML-powered features, enabling fast iteration and efficient experimentation with novel features.

Required Skills and Qualifications:

• 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.