AI/ML Engineer

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Requirements:

• Minimum of 3+ years’ experience in data science/ML role, with a track record of delivering impactful solutions in a production environment.
• Proficiency in programming languages like Python, R, and SQL, with experience in building scalable and efficient ML/NLP workflows.
• Deep understanding and hands on experience in Machine Learning, Deep Learning, and Natural Language Processing.
• Experience in working with state-of-the-art Generative AI models, including model finetuning and evaluation techniques.
• Data management knowledge, including data pre-processing, augmentation, and generation of synthetic data.
• Cloud computing and deployment knowledge for deploying and managing AI applications on cloud platforms like AWS, Google Cloud, or Microsoft Azure.

Responsibilities:

• Develop, optimize, and deploy machine learning and deep learning models, including LLMs and Generative AI models.
• Design and implement scalable, production-ready AI solutions that integrate into existing systems.
• Fine-tune and evaluate models on large-scale datasets to improve accuracy, efficiency, and robustness.
• Collaborate with software engineers, data scientists, and product teams to align AI models with business needs.
• Work with healthcare and claims data to build high-performance AI systems.
• Develop and maintain MLOps pipelines for training, deploying, and monitoring AI models.
• Troubleshoot and resolve AI/ML engineering challenges, ensuring models perform effectively in production.
• Stay up-to-date with advancements in Generative AI, LLMs, and deep learning to continuously improve AI solutions.
• Document AI/ML workflows, methodologies, and best practices for internal knowledge sharing.