Senior Machine Learning Engineer

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.

If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi

Years of experience: 3+ yrs (3 yrs to 10 yrs)

Location: Bangalore - Hybrid only
 

We are seeking a skilled and passionate ML Engineer with 3+ years of advanced ML Ops framework deployment 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 Databricks, and MLflow to build robust and scalable ML solutions.

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 Databricks, leveraging services like ML Flow, Github actions , Unity Catalog, Databricks asset bundle

• Hands on exposure in using Databricks workflow as an orchestrator to create multi task workflows for trainings and inference pipelines

• Experience in handling Mosaic AI model serving and leverage lakehouse monitoring for model drift

• 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.

• Education: Bachelor's or Master's Degree in Computer Science, Engineering, Statistics, or a related quantitative field.

• Experience: Minimum 3+ years of professional experience as an ML Engineer or in a similar role.

• 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.

• 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).

• Microsoft Certified: Azure AI Engineer Associate

• Databricks Certified Machine Learning Associate (or higher)

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us