
AI Engineering Director
2 weeks ago
The AI Manager plays a key role in leading the AI team, contributing to technical strategy and decision-making. This position involves managing the day-to-day delivery of the AI/ML team, responsible for building, deploying, and maintaining robust, scalable, and efficient ML models.
Key Responsibilities:- Provide technical guidance and strategic direction for the AI team, aligning with overall business 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 cross-functional 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 stakeholders, 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 teams (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.
- Communicate effectively with team members, 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 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 relevant domains with at least 3+ years of experience.
- 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 cloud platforms.
- 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.
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