Machine Learning Engineer

We are looking for a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). Your responsibilities will include automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will collaborate with technical teams to develop cutting-edge machine learning systems that drive business value. In this role, you will manage the deployment and maintenance of machine learning models in production environments, ensuring seamless integration with existing systems. You will monitor model performance using metrics such as accuracy, precision, recall, and F1 score, addressing issues like performance degradation, drift, or bias. Troubleshooting problems, maintaining documentation, and managing model versions for audit and rollback will be part of your routine tasks. Your duties will also involve analyzing monitoring data proactively to identify potential issues and providing regular performance reports to stakeholders. Additionally, you will focus on optimizing queries and pipelines, as well as modernizing applications when necessary. To qualify for this role, you should have expertise in programming languages like Python and SQL, along with a solid understanding of best MLOps practices for deploying enterprise-level ML systems. Familiarity with Machine Learning concepts, models, and algorithms, such as regression, clustering, and neural networks, including deep learning and transformers, is essential. Experience with GCP tools like BigQueryML, Vertex AI Pipelines, Model Versioning & Registry, Cloud Monitoring, and Kubernetes is preferred. Strong communication skills, both written and oral, are crucial, as you will be required to prepare detailed technical documentation for new and existing applications. You should demonstrate strong ownership and collaborative qualities in your domain, taking the initiative to identify and drive opportunities for improvement and process streamlining. A Bachelor's Degree in a quantitative field or equivalent job experience is required for this position. Experience in Azure MLOPS, familiarity with Cloud Billing, setting up or supporting NLP, Gen AI, LLM applications with MLOps features, and working in an Agile environment are considered bonus qualifications. If you are passionate about MLOps, have a knack for problem-solving, and enjoy working in a collaborative environment to deliver innovative machine learning solutions, we would like to hear from you.,