AI/ML Ops Engineer

The primary responsibility of this role involves designing, developing, and implementing generative AI models and algorithms using cutting-edge techniques like GPT, VAE, and GANs. You will collaborate with cross-functional teams to define project requirements in line with business goals. Staying updated with the latest advancements in generative AI, machine learning, and deep learning is crucial for identifying opportunities to enhance our products and services. Additionally, you will be optimizing existing AI models for better performance, scalability, and efficiency. Developing and maintaining AI pipelines, including data preprocessing, feature extraction, model training, and evaluation, is also a key aspect of this role. Clear and concise documentation will be essential to communicate complex AI concepts to both technical and non-technical stakeholders. Furthermore, you will contribute to establishing best practices and standards for generative AI development within the organization. Providing technical mentorship and guidance to junior team members, ensuring trusted AI practices, and driving DevOps and MLOps practices are also part of the responsibilities. Utilizing tools like Docker, Kubernetes, and Git for building and managing AI pipelines, implementing monitoring and logging tools for AI model performance and reliability, and collaborating seamlessly with software engineering and operations teams for efficient AI model integration and deployment are essential tasks. Familiarity with DevOps and MLOps practices, continuous integration, deployment, and monitoring of AI models will be advantageous. The ideal candidate for this role should have a minimum of 5 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques is required. Proficiency in programming languages like Python, R, and frameworks such as TensorFlow or PyTorch is essential. A strong understanding of NLP techniques and frameworks like BERT, GPT, or Transformer models is necessary. Familiarity with computer vision techniques, cloud platforms like Azure or AWS, data engineering, and trusted AI practices is also crucial. Strong collaboration skills with software engineering and operations teams, problem-solving abilities, and the capability to translate business requirements into technical solutions are key qualifications for this role. Excellent communication and interpersonal skills, along with a track record of driving innovation and staying updated with the latest AI research and advancements, are essential. A degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field is required, with a Master's degree preferred. Solid experience in developing and implementing generative AI models, proficiency in Python, experience with machine learning libraries and frameworks, strong knowledge of data structures, algorithms, and software engineering principles, familiarity with cloud-based platforms, and experience with NLP techniques and tools are also desired qualifications for this position.,