Architect - MLOps & Databricks

2 weeks ago

Bengaluru Karnataka India, Karnataka 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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