Architect - Mlops & Databricks

16 hours ago

Yelahanka, India Quantiphi Full time

We are seeking a skilled and passionate ML Engineer with 7+ years of experience to join our team. The ideal candidate will be instrumental in developing, deploying, and maintaining machine learning models, with a strong focus on MLOps practices. This role requires hands-on experience with Azure cloud services, Databricks, and MLflow to build robust and scalable ML solutions. Location : Bangalore (Current or open to relocate) Workplace : Hybrid (3 days WFO) Responsibilities: ● Design, develop, and implement machine learning models and algorithms to solve complex business problems. ● Collaborate with data scientists to transition models from research and development to production-ready systems. ● Build and maintain scalable data pipelines for ML model training and inference using Databricks. ● Implement and manage the ML model lifecycle using MLflow for experiment tracking, model versioning, and model registry. ● Deploy and manage ML models in production environments on Azure, leveraging services like Azure Machine Learning, Azure Kubernetes Service (AKS), or Azure Functions. ● Support MLOps workloads by automating model training, evaluation, deployment, and monitoring processes. ● Ensure the reliability, performance, and scalability of ML systems in production. ● Monitor model performance, detect drift, and implement retraining strategies. ● Collaborate with DevOps and Data Engineering teams to integrate ML solutions into existing infrastructure and CI/CD pipelines. ● Document model architecture, data flows, and operational procedures. Qualifications: ● Education: Bachelor’s or Master’s Degree in Computer Science, Engineering, Statistics, or a related quantitative field. Skills: ● Strong proficiency in Python programming for data manipulation, machine learning, and scripting. ● Hands-on experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, or Keras. ● Demonstrated experience with MLflow for experiment tracking, model management, and model deployment. ● Proven experience working with Microsoft Azure cloud services, specifically Azure Machine Learning, Azure Databricks, and related compute/storage services. ● Solid experience with Databricks for data processing, ETL, and ML model development. ● Understanding of MLOps principles and practices, including CI/CD for ML, model versioning, monitoring, and retraining. ● Experience with containerization technologies (Docker) and orchestration (Kubernetes, especially AKS) for deploying ML models. ● Familiarity with data warehousing concepts and SQL. ● Ability to work with large datasets and distributed computing frameworks. ● Strong problem-solving skills and attention to detail. ● Excellent communication and collaboration skills. Nice-to-Have Skills: ● Experience with other cloud platforms (AWS, GCP). ● Knowledge of big data technologies like Apache Spark. ● Experience with Azure DevOps for CI/CD pipelines. ● Familiarity with real-time inference patterns and streaming data. ● Understanding of responsible AI principles (fairness, explainability, privacy). Certifications: ● Microsoft Certified: Azure AI Engineer Associate ● Databricks Certified Machine Learning Associate (or higher)

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