ML Engineer

As a Machine Learning Engineer at Tiger Analytics, you will be working on a variety of cutting-edge data analytics and machine learning problems across different industries. Your main responsibilities will include: - Collaborating with data scientists to transition machine learning models from development to production. - Designing and implementing MLOps pipelines for model training, deployment, and monitoring on GCP. - Utilizing GCP services for version control, continuous integration, and continuous deployment (CI/CD) of machine learning models. - Implementing monitoring and logging solutions to track the performance and health of deployed models. - Optimizing and scaling machine learning workflows on GCP to handle production workloads efficiently. - Staying updated on the latest developments in MLOps practices and GCP services to ensure best practices are followed. To be successful in this role, you should have the following qualifications and skills: - 3+ years of experience with at least 3+ years of relevant Data Science experience. - Good working knowledge of GCP. - Proficiency in structured Python. - Experience in following good software engineering practices and interest in building reliable and robust software. - Good knowledge of Data Science concepts and professional experience in developing and enhancing algorithms and models to solve business problems. - Ability to conduct quantitative analyses and interpret results. - Working knowledge of Linux or Unix environments, ideally in a cloud environment. - Working knowledge of Spark/PySpark is desirable. - Excellent written and verbal communication skills. - B.Tech from Tier-1 college / M.S or M. Tech is preferred. Join Tiger Analytics, a global AI & analytics consulting firm, and be part of an AI revolution. Your expertise will be valued, and you will have the opportunity to work with teams that push boundaries and inspire innovation. Tiger Analytics offers competitive compensation packages and believes in equal opportunities for all. Come be a part of building the world's best AI and advanced analytics team. As a Machine Learning Engineer at Tiger Analytics, you will be working on a variety of cutting-edge data analytics and machine learning problems across different industries. Your main responsibilities will include: - Collaborating with data scientists to transition machine learning models from development to production. - Designing and implementing MLOps pipelines for model training, deployment, and monitoring on GCP. - Utilizing GCP services for version control, continuous integration, and continuous deployment (CI/CD) of machine learning models. - Implementing monitoring and logging solutions to track the performance and health of deployed models. - Optimizing and scaling machine learning workflows on GCP to handle production workloads efficiently. - Staying updated on the latest developments in MLOps practices and GCP services to ensure best practices are followed. To be successful in this role, you should have the following qualifications and skills: - 3+ years of experience with at least 3+ years of relevant Data Science experience. - Good working knowledge of GCP. - Proficiency in structured Python. - Experience in following good software engineering practices and interest in building reliable and robust software. - Good knowledge of Data Science concepts and professional experience in developing and enhancing algorithms and models to solve business problems. - Ability to conduct quantitative analyses and interpret results. - Working knowledge of Linux or Unix environments, ideally in a cloud environment. - Working knowledge of Spark/PySpark is desirable. - Excellent written and verbal communication skills. - B.Tech from Tier-1 college / M.S or M. Tech is preferred. Join Tiger Analytics, a global AI & analytics consulting firm, and be part of an AI revolution. Your expertise will be valued, and you will have the opportunity to work with teams that push boundaries and inspire innovation. Tiger Analytics offers competitive compensation packages and believes in equal opportunities for all. Come be a part of building the world's best AI and advanced analytics team.