Company Description Digizac Solutions is an ISO certified agile and creative IT company based in Pune We provide top-notch IT hardware and software solutions to corporate clients tailored to their unique requirements Our offerings include hardware procurement and installation software development and implementation network maintenance and management cyber security solutions cloud computing services data management and annual maintenance contracts We strive to build long-term relationships with our clients by providing timely support and superior customer service Role Description Summary It s a unique role for an individual passionate about both the operational and scientific aspects of machine learning Your primary focus approx 80 will be on designing building and maintaining our robust MLOps infrastructure on Google Cloud Platform GCP with a strong emphasis on the Vertex AI suite The rest of your time approx 20 will involve hands-on data science work including model refinement feature engineering and training ensuring a seamless transition from research to production This role will be a critical link between our data science and engineering teams responsible for the entire lifecycle of ML models Responsibilities Architect and build the end-to-end MLOps infrastructure using GCP services Leverage Vertex AI Pipelines Experiments and Model Registry to create reproducible and governable ML workflows Create and manage CI CD pipelines using tools like Cloud Build Jenkins or GitLab CI for the automated building testing containerization and deployment of ML models to Vertex AI Endpoints Implement automated systems for deploying new model versions to Vertex AI Endpoints for both online and batch predictions Configure and manage auto-scaling to handle variable demand efficiently Package ML models and dependencies into Docker containers and manage their deployment and lifecycle within Google Kubernetes Engine GKE Implement and manage all cloud infrastructure using Infrastructure as Code IaC tools like Terraform or CloudFormation to ensure consistency reproducibility and version control Implement robust monitoring using Cloud Monitoring and Cloud Logging Analyse and optimize model serving infrastructure for performance scalability and cost-efficiency Implement security best practices for protecting models data and infrastructure using GCP IAM service accounts and VPC service controls Work within Vertex AI Workbench managed notebooks to refine test and package models developed by the data science team ensuring they meet production performance and code quality standards Collaborate on designing and implementing feature engineering pipelines using BigQuery Dataflow and the Vertex AI Feature Store to create a centralized repository of reusable production-ready features Utilize Vertex AI Training to run custom training jobs at scale Leverage the hyperparameter tuning service to optimize model performance Act as the primary technical liaison between data scientists and the data platform team Translate research models and notebooks into robust production-ready code and components for ML pipelines Qualifications Bachelor s or master s degree in computer science Data Science Statistics or a related quantitative field 3 years of hands-on experience in a data science role building and shipping machine learning models to production Strong understanding and hands-on experience with cloud platforms e g AWS Azure GCP and their services for machine learning Extensive experience with containerization e g Docker and container orchestration e g Kubernetes Proficiency in Infrastructure as Code IaC tools e g Terraform CloudFormation Experience with CI CD tools and practices e g Git Jenkins GitLab CI Experience with monitoring and logging tools e g Prometheus Grafana ELK stack Solid understanding of SQL and experience working with large-scale data warehouses like Google BigQuery Excellent problem-solving skills and the ability to work independently and in a team environment Strong communication and collaboration skills Preferred Qualifications Google Cloud Professional Machine Learning Engineer or Professional Cloud DevOps Engineer certification Strong understanding of networking and security concepts Experience with advanced model serving concepts like custom prediction routines in Vertex AI or KServe on GKE Familiarity with large-scale petabyte-scale data processing frameworks Job Type Full-time Pay 150 000 00 - 2 500 000 00 per year Benefits Provident Fund Work Location In person

📌 Mlops Engineer (with Data Science Focus) - Vertex Ai Specialist (Maharashtra)
🏢 Digizac Solutions India Private
📍 Maharashtra