Machine Learning Engineer - Databricks

Job Title : Machine Learning Engineer - Databricks

Location : Chennai / Bangalore

Experience : 3+ Years

Notice Period : Immediate joiner or serving notice (- 60 days)

About The Role We are seeking a skilled Machine Learning Engineer with hands-on experience in building and deploying end-to-end ML workflows on Databricks. The ideal candidate will work closely with enterprise clients to develop, train, deploy, and monitor machine learning models at scale using Databricks-native tools such as MLflow and Mosaic AI.

Key Responsibilities

• Design, develop, and deploy scalable end-to-end machine learning pipelines on Databricks
• Build, train, and optimize ML models using distributed compute frameworks
• Implement experiment tracking, model versioning, and lifecycle management using MLflow
• Engineer and manage reusable features using Databricks Feature Store
• Deploy models for real-time and batch inference using Databricks Model Serving
• Leverage AutoML for baseline model development and feature importance analysis
• Perform distributed training using Spark MLlib, XGBoost, and Horovod
• Conduct hyperparameter tuning at scale using Hyperopt
• Monitor model performance, data quality, and drift using Lakehouse Monitoring
• Collaborate with data engineers, product teams, and clients to translate business problems into ML solutions
• Prepare clear technical documentation and communicate effectively with stakeholders

Technical Skills Required Candidates should have experience in 6- 8 of the following :

• MLflow (experiment tracking, model registry, model versioning)
• Databricks Feature Store for feature engineering and reuse
• Databricks Model Serving (real-time and batch inference)
• AutoML for baseline model creation
• Distributed ML using Spark MLlib, XGBoost, and Horovod
• PyTorch and/or TensorFlow on Databricks (single-node and distributed training)
• Hyperopt for scalable hyperparameter tuning
• Lakehouse Monitoring for model drift and data quality tracking

Experience & Qualifications

• 3+ years of experience in Machine Learning Engineering
• At least 1 year of hands-on experience deploying ML models on Databricks
• Proven delivery of 2+ production-grade ML models with MLflow tracking and serving
• Strong understanding of ML lifecycle management and MLOps best practices
• Excellent communication skills for client interaction and technical documentation

Nice To Have

• Experience working with enterprise clients
• Exposure to Mosaic AI and advanced Databricks ML capabilities
• Familiarity with cloud platforms and large-scale data systems

(ref:hirist.tech)