Senior AI Engineer

Tiger Analytics is seeking a highly skilled Senior AI Engineer to join our dynamic team. In this role, you will design, develop, and implement cutting-edge AI solutions that drive business value for our clients. You will leverage advanced machine learning techniques, frameworks, and large datasets to create innovative products and solutions. As a Senior AI Engineer, you will work closely with cross-functional teams to identify project requirements, define success metrics, and maintain high-quality standards. Your expertise in AI will play a critical role in shaping our product offerings and ensuring the successful deployment of AI models in production. The successful candidate will have a solid background in artificial intelligence, experience with various ML frameworks, and a passion for solving complex business problems. Requirements Key Responsibilities:

• Design and implement AI algorithms and models to solve real-world problems.
• Collaborate with data scientists, data engineers, and business analysts to understand project requirements and propose relevant AI solutions.
• Monitor and analyze the performance of AI models in production and iterate on them to improve outcomes.
• Develop technical documentation as well as customer-facing documentation and presentations.
• Stay updated with the latest research and trends in AI and propose innovative ideas to improve our offerings.

• Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 5+ years of experience in AI/ML development with demonstrated success in deploying machine learning models to production.
• Proficiency in programming languages such as Python and familiarity with libraries such as TensorFlow, PyTorch, and Scikit-learn.
• Experience with cloud-based AI services such as AWS, Google Cloud, or Azure.
• Strong analytical and problem-solving skills, with a proven ability to interpret business requirements into technical solutions.
• Excellent communication skills and ability to convey complex technical concepts to non-technical stakeholders.

• Experience with natural language processing (NLP) or computer vision applications.
• Knowledge of MLOps principles and tools.
• Familiarity with version control systems (e.g., Git) and Agile methodologies.

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