Senior Engineer- MLOps + GCP

As an MLOps Engineer at Fractal Analytics, you will be tasked with collaborating with Data Scientists and Data Engineers to deploy and operate advanced analytics machine learning models. Your responsibilities will include: - Enabling model tracking, model experimentation, and model automation - Developing scalable ML pipelines - Building MLOps components in the machine learning development lifecycle using Model Repository such as MLFlow or Kubeflow Model Registry - Utilizing Machine Learning Services like Kubeflow, DataRobot, HopsWorks, Dataiku, or any relevant ML E2E PaaS/SaaS - Working across all phases of the model development lifecycle to construct MLOPS components - Establishing the knowledge base necessary to deliver increasingly complex MLOPS projects on the Cloud, particularly on GCP - Playing an integral role in client business development and delivery engagements across multiple domains Qualifications required for this role include: - 5-9 years" experience in building production-quality software - Strong background in System Integration, Application Development, or Data Warehouse projects across technologies used in the enterprise space - Basic knowledge of MLOps, machine learning, and Docker - Proficiency in object-oriented languages such as Python, PySpark, Java, C#, and C++ - Experience in developing CI/CD components for production-ready ML pipelines - Database programming skills using SQL - Knowledge of Git for source code management - Ability to collaborate effectively with highly technical resources in a fast-paced environment - Problem-solving skills, project management abilities, and excellent communication - Foundational knowledge of Cloud Computing on GCP - Hunger and passion for learning new skills Education required for this position: - B.E/B.Tech/M.Tech in Computer Science or related technical degree OR Equivalent,