Senior AI Engineer

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Requirements:

• Master’s degree in Computer Science, Machine Learning, Statistics, Engineering, Mathematics, or a related field
• Deep understanding and practical experience in machine learning and natural language processing, especially with deep learning architectures
• Strong foundational knowledge in statistical modeling, probability, and linear algebra
• Extensive practical experience with curating datasets, training models, analyzing post-deployment data, and developing robust metrics to ensure model reliability
• Experience developing and maintaining machine learning services for real-world applications at scale
• Strong Python programming skills and ability to write maintainable, production-ready code
• Proficiency with Container Orchestration services such as Docker
• Proficiency with AWS, including Serverless
• Proven track record in driving AI projects with strong technical leadership.
• Excellent communication skills when engaging with both technical and non-technical stakeholders
• Proactive attitude with a continuous improvement mindset, seeking help and providing feedback when necessary

Responsibilities:

• Develop innovative, scalable AI solutions for real business problems.
• Drive the full lifecycle of projects from conception to deployment, ensuring alignment with business objectives.
• Manage complex data sets, design efficient data processing pipelines, and train robust models.
• Own highly open-ended projects end-to-end, from the analysis of business requirements to the deployment of solutions.
• Work closely with other AI engineers, product managers, and stakeholders to ensure that AI solutions meet business needs and enhance user satisfaction.
• Write clear, concise, and comprehensive technical documentation for all projects and systems developed.
• Stay updated on the latest developments in the field. Explore and prototype new technologies and approaches to address specific challenges faced by the business.
• Develop and maintain high-quality machine learning services. Prioritize robust engineering practices and user-centric development.