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Data Engineer / Data Scientist – MLOps & Machine Learning
Overview
Seeking a highly analytical and hands-on Data Engineer / Data Scientist with strong MLOps experience in Databricks environments. This role requires a strong foundation in machine learning theory, model development, and large-scale cloud-based data platforms. The ideal candidate should be comfortable working across engineering and data science teams while supporting end-to-end ML workflows in production environments.
Must Haves
- 5+ years of hands-on experience as a Data Engineer or Data Scientist in large-scale, cloud-based data environments
- Strong experience building or supporting MLOps workflows in Databricks
- Hands-on experience with MLflow, including experiment tracking, model registry, and deployment workflows
- Strong understanding of machine learning fundamentals and model lifecycle management
- Solid data science foundation with understanding of ML theory, mathematics, and statistical concepts
- Experience building, training, validating, and deploying machine learning models
- Ability to explain model selection decisions and ML approaches clearly
- Strong collaboration and communication skills with the ability to work well across cross-functional teams
- Strong personality fit and ability to work effectively in team-oriented environments
- Willingness to work onsite
Responsibilities
- Design, build, and support scalable machine learning and data workflows in cloud environments
- Develop and maintain MLOps pipelines using Databricks and MLflow
- Track, manage, and deploy machine learning models across environments
- Work closely with data scientists, engineers, and business stakeholders to deliver ML-driven solutions
- Analyze large datasets and apply machine learning techniques to solve business problems
- Support model monitoring, optimization, and continuous improvement initiatives
- Collaborate on architecture, best practices, and scalable ML engineering standards
Interested candidates may submit their resumes online or call at 310-906-4780 for further information regarding the position.
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