Managerial Skills:

·       Lead and manage data science & AI operations and projects, ensuring they are delivered in accordance with client commitments and expectations.

·       Provide technical guidance and mentorship to AI engineers, data scientists, and team members.

·       Contribute to departmental strategy and objectives while ensuring alignment with the organization's goals.

·       Foster a collaborative and growth-oriented team environment that promotes continuous learning and experimentation.

Technical Skills:

·       Lead the design, development, and deployment of AI and machine learning models for various use cases, such as predictive analytics, natural language processing (NLP), computer vision, or recommendation systems.

·       Oversee the implementation of AI-driven solutions in production environments, ensuring scalability, robustness, and efficiency.

·       Evaluate and implement emerging AI/ML technologies and best practices to ensure state-of-the-art solutions.

·       Collaborate with data engineering teams to ensure efficient data pipelines, model training, and deployment processes.

·       Drive efforts in MLOps, ensuring continuous integration and delivery (CI/CD) of AI models.

·       Ensure data quality, governance, and security in AI models and solutions.

·       Develop AI roadmaps and prioritize AI projects based on business needs and impact.

·       Collaborate with product managers and stakeholders to define requirements, goals, and expected outcomes for AI projects.

Basic Qualifications:

·       Typically, 8+ years of relevant work experience, with a minimum of 3+ years in a similar AI leadership role.

·       Proven experience in leading projects and operations, including model development, deployment, and monitoring with expertise in AI/ML:

o   Proficient in Python, R, Scala with experience in cloud AI platforms (AWS, Azure, Google Cloud AI).

o   Strong understanding of deep learning, reinforcement learning, NLP, and generative AI technologies, including large language models (LLMs), fine-tuning techniques, and advanced prompt engineering

o   Experience with RAG based solutions architecture

o   Proven experience in MLOps, including the implementation of automated pipelines, model deployment, monitoring, and continuous integration/continuous delivery (CI/CD) for machine learning models

Other Qualifications:

·       Excellent communication skills with the ability to articulate complex AI concepts to non-technical stakeholders.

·       Strong problem-solving and analytical thinking, with a focus on delivering value through AI-driven innovation.

·       Relevant certifications in AI or cloud platforms (Microsoft, AWS, Google).

·       Advanced degree (Master's or Ph.D.) in Computer Science, AI, Machine Learning, or a related field is a plus.

·       Fluency in English and French; proficiency in another language is a plus.