Platform Engineer II

As an experienced professional in Machine Learning and Deep Learning, you will be responsible for designing and implementing solutions in various areas. Your key responsibilities will include: - Minimum 5 years of experience in Machine Learning and predictive analytics - Hands-on experience in developing models using technologies such as Keras, TensorFlow, pyTorch, and GCP AI/ML services - Proficiency in Python, Spark, and relevant libraries like TensorFlow, Spark ML, scikit-learn, pandas, and NumPy - Software engineering skills in Python, including building libraries and deploying Python codes in production - Experience in model deployment and monitoring on public clouds like AWS, Azure, or GCP, with GCP experience being an added advantage - Previous exposure to handling Supervised Learning, Unsupervised learning, and Reinforcement learning problems in various industry verticals - Transforming data science prototypes into scalable products for seamless production deployment - Implementation of CI/CD principles in the Machine Learning domain (ML Ops) - Familiarity with containers and orchestration (Kubernetes) - Proficiency in Google Cloud Platform services such as BigQuery, Cloud Composer, Vertex AI, and AI/ML services in general - Strong grasp of statistical concepts and expertise in Machine Logs processing, text mining, and text analytics In addition to your technical skills, you are expected to possess core competencies such as strong communication and presentation skills, an analytical and client-first mindset, leadership and stakeholder management abilities, and the capability to thrive in a global, fast-paced environment. Please note that the job description does not contain any additional details about the company. As an experienced professional in Machine Learning and Deep Learning, you will be responsible for designing and implementing solutions in various areas. Your key responsibilities will include: - Minimum 5 years of experience in Machine Learning and predictive analytics - Hands-on experience in developing models using technologies such as Keras, TensorFlow, pyTorch, and GCP AI/ML services - Proficiency in Python, Spark, and relevant libraries like TensorFlow, Spark ML, scikit-learn, pandas, and NumPy - Software engineering skills in Python, including building libraries and deploying Python codes in production - Experience in model deployment and monitoring on public clouds like AWS, Azure, or GCP, with GCP experience being an added advantage - Previous exposure to handling Supervised Learning, Unsupervised learning, and Reinforcement learning problems in various industry verticals - Transforming data science prototypes into scalable products for seamless production deployment - Implementation of CI/CD principles in the Machine Learning domain (ML Ops) - Familiarity with containers and orchestration (Kubernetes) - Proficiency in Google Cloud Platform services such as BigQuery, Cloud Composer, Vertex AI, and AI/ML services in general - Strong grasp of statistical concepts and expertise in Machine Logs processing, text mining, and text analytics In addition to your technical skills, you are expected to possess core competencies such as strong communication and presentation skills, an analytical and client-first mindset, leadership and stakeholder management abilities, and the capability to thrive in a global, fast-paced environment. Please note that the job description does not contain any additional details about the company.