ML Engineer: Production ML & MLOps (Databricks)

Inceed; Dallas (TX); On-site; USD 112,000 - 140,000; Full time

Job summary

Inceed partners with a Dallas‑based team to hire a hands‑on Machine Learning Developer. You will move models from experimentation into reliable production, building scalable MLOps processes and collaborating with data science, engineering, and business teams to deliver impactful ML solutions.

This onsite role in Dallas offers a competitive package with responsibilities spanning model deployment, monitoring, and lifecycle management, plus a compensation range of $112,000–$140,000 annually based

Qualifications

• Bachelor’s degree in a related technical field.
• Hands‑on experience with Databricks MLflow and AutoML.
• Three to five years of production ML or data systems experience.
• Strong Python development skills with tested, maintainable code.
• Strong SQL skills and working knowledge of Spark.
• Experience with MLOps workflows and model lifecycle management.
• Solid understanding of Git, unit testing, and CI/CD.
• Ability to explain ML concepts and model tuning practices.

Responsibilities

• Build MLOps standards and reusable production pipeline patterns.
• Productionize models using Databricks tools and workflows.
• Design CI/CD pipelines for model training and deployment.
• Manage model tracking, registration, versioning, and lineage.
• Implement monitoring, validation, and operational observability.
• Strengthen data and feature quality through schema checks.
• Create documentation, reference guides, and playbooks.
• Partner with teams to align requirements and drive adoption.

Skills

Python development

SQL proficiency

Git & CI/CD

MLOps concepts

Explain ML concepts

Education

Bachelor’s degree in a related technical field

Tools

Databricks MLflow

AutoML

Spark

Unity Catalog

Containerization tools

Databricks certification (ML)

Job description

Inceed partners with a Dallas‑based team to hire a hands‑on Machine Learning Developer. You will move models from experimentation into reliable production, building scalable MLOps processes and collaborating with data science, engineering, and business teams to deliver impactful ML solutions.

This onsite role in Dallas offers a competitive package with responsibilities spanning model deployment, monitoring, and lifecycle management, plus a compensation range of $112,000–$140,000 annually based