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YOU TASKS AND RESPONSIBILITES


Drive the strategic vision for AI Engineering, leading cross-functional teams in the design, architecture and implementation of cutting-edge machine learning models and algorithms to tackle complex business challenges.
Lead or oversee the development and deployment of scalable AI products, ensuring they align with organizational goals and deliver measurable value.
Champion the use of state-of-the-art cloud technologies (e.g., AWS, Azure, Google Cloud) to enhance and promote the industrialization and operationalization of machine learning models and AI solutions across the organization.
Provide expert guidance and mentorship on the operational support of machine learning models and algorithms, ensuring their reliability, performance, and scalability in production environments.
Lead the architecture and design of robust, scalable data pipelines in collaboration with data engineers, cloud engineers, and data scientists, enhancing data access and processing capabilities.
Lead initiatives in data preprocessing, ingestion, and transformation activities across hybrid environments (both on-premises and cloud), ensuring adherence to best practices and organizational standards.
Establish and promote comprehensive data quality assurance processes, including validation checks and data drift detection mechanisms, to ensure data consistency and integrity.
Mentor and guide team members in the model training process, focusing on industrialization through cloud technologies and achieving accuracy, reliability through experimentation and iterative improvements
Lead the evaluation and tuning of models, utilizing comprehensive metrics and performance benchmarks to refine algorithms and enhance predictive capabilities, ensuring alignment with business objectives.
Lead the integration of AI models into existing software systems and workflows, ensuring seamless functionality, performance, and optimal user experience.
Direct the deployment of AI solutions into production environments, defining and implementing architecture best practices to ensure operational excellence
Maintain comprehensive documentation of AI models, algorithms, solution architecture and processes to ensure transparency and facilitate knowledge sharing within the team.
Engage proactively with team members and stakeholders to gather requirements, provide insights, and deliver effective AI solutions that align with project goals and organizational strategy.
Communicate complex AI concepts and results effectively to both technical and non-technical (senior) stakeholders, fostering understanding, collaboration, and informed decision-making.
Act as a leader or technical specialist, providing detailed support and guidance within the organization and helping colleagues to develop skills
Drive initiatives to stay abreast of emerging AI trends, technologies, and methodologies, actively contributing to the enhancement of team capabilities and innovation.
Conduct research and experimentation to explore new AI techniques and approaches, providing strategic insights that can inform future projects and initiatives


WHO YOU ARE


Master’s or Ph.D. degree in Computer Science, Information Technology, Data Science, Artificial Intelligence or a related field or Bachelor’s with minimum 10 years experience.
Proven experience as an AI Engineer, Machine Learning Engineer, or similar role.
Experience in developing and deploying machine learning models and AI systems.
Proficiency in programming languages such as Python or R
Strong knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
Experience with natural language processing (NLP), computer vision, and other AI techniques.
Familiarity with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud)
Experience with industrializing machine learning and AI use cases utilizing cloud-native services (AWS SageMaker, Azure ML)
Strong analytical skills and the ability to work with complex datasets.
Excellent problem-solving skills with a focus on developing innovative AI solutions.
Excellent verbal and written communication skills.
Ability to work collaboratively in a cross-functional team environment.
Strong organizational skills and the ability to manage multiple AI projects simultaneously.
Experience with Agile methodologies and tools (Azure DevOps, Scrum).
Relevant certifications in AI, machine learning, or data science (e.g., AWS Certified Machine Learning or Solutions Architect, Azure AI Engineer)


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