[Remote] MLOps Engineer – Azure Databricks & MLflow
Note: The job is a remote job and is open to candidates in USA. ICONMA is an IT Services and Consulting company seeking an MLOps Engineer specializing in Azure Databricks and MLflow for a remote position. The role involves building end-to-end data and ML solutions, managing data pipelines, and applying MLOps principles to enhance model development and deployment.
Responsibilities
- At least 5 years of experience in a relevant discipline area is required
- Knowledge of the latest technologies and trends in data engineering are highly preferred and includes:
- At least 5 years of experience in data engineering with a strong background on Azure Databricks and Scala/Python
- Experience in handling unstructured data processing and transformation with programming knowledge
- Hands on experience in building data pipelines using Scala/Python
- Big data technologies such as Apache Spark, Structured Streaming, Advanced SQL, Databricks, Delta Lake, Azure/AWS
- Strong analytical and problem-solving skills with the ability to troubleshoot spark applications and resolve data pipeline issues
- Familiarity with version control systems like Git, CICD pipelines
- Experience with Azure Databricks and MLflow
- Good understanding of ML workflows, model development, and evaluation
- Knowledge of MLOps fundamentals such as CI/CD, versioning, and monitoring
- Ability to build end-to-end data and ML solutions
- Exposure to production ML or AI systems
- Understanding of data engineering and data modeling basics
- Ability to work independently on loosely defined problems
- Strong problem-solving and communication skills
- Mentoring experience is a plus
Skills
- At least 5 years of experience in a relevant discipline area is required
- At least 5 years of experience in data engineering with a strong background on Azure Databricks and Scala/Python
- Experience in handling unstructured data processing and transformation with programming knowledge
- Hands on experience in building data pipelines using Scala/Python
- Big data technologies such as Apache Spark, Structured Streaming, Advanced SQL, Databricks, Delta Lake, Azure/AWS
- Strong analytical and problem-solving skills with the ability to troubleshoot spark applications and resolve data pipeline issues
- Familiarity with version control systems like Git, CICD pipelines
- Experience with Azure Databricks and MLflow
- Good understanding of ML workflows, model development, and evaluation
- Knowledge of MLOps fundamentals such as CI/CD, versioning, and monitoring
- Ability to build end-to-end data and ML solutions
- Exposure to production ML or AI systems
- Understanding of data engineering and data modeling basics
- Ability to work independently on loosely defined problems
- Strong problem-solving and communication skills
- Mentoring experience is a plus
Benefits
- Health Benefits
- Referral Program
- Excellent growth and advancement opportunities
Company Overview