Engineer, Data Engineer

Databricks Machine Learning Engineer

Must Have Technical/Functional Skills We are looking for a highly skilled and passionate Databricks Machine Learning Engineer to build scalable ML pipelines, automating training and deployment, managing model lifecycle with MLflow.

• Collaborate closely with data scientists, data engineers, and business stakeholders to gather requirements and understand the business objectives driving model development.
• Develop various methods for implementing feature engineering techniques; preprocess and transform large datasets, selecting appropriate algorithms.
• Leverage Databricks MLflow for experiment tracking and model management.
• Build robust pipelines that automate the training, validation, and deployment of models.
• Monitor model performance and collaborate closely with data scientists and stakeholders to fine‑tune models.
• Migrate on‑prem PySpark, SAS data pipelines and ML models to Databricks.
• Define and implement ML best practices in Databricks.
• Evaluate new Databricks ML features and tools, helping the organization stay at the forefront of innovation in AI and Big Data.
• Explore AI and Gen AI solutions for business requirements and implement various solutions.

• Proven expertise in implementing various ML models using Databricks.
• Strong PySpark and Python experience.
• Familiarity with ML Ops/LLM Ops and distributed systems.
• Experience with Big Data platforms such as Cloudera Hadoop and cloud platforms like AWS, GCP.
• Solid understanding of system design patterns, scalability, observability, and performance tuning.
• Strong analytical and problem‑solving skills.
• Passion for exploring and building with emerging technologies.

Salary Range- $100,000-$130,000 a year