Compunnel Inc.

Senior ML Engineer Deployment and Databricks MLOps

Austin, Texas, USA · Senior · Contract

Sponsorship not specifiedDetected 41 days ago

PythonGitDatabricksCloud PlatformsCI/CDMachine LearningData EngineeringData ScienceMLOpsAI OrchestrationTest AutomationUnityResearchProblem Solving

About the role

The ideal candidate combines strong software engineering expertise with hands-on experience in machine learning operations and cloud-based data platforms.

Design, develop, and maintain reusable ML workflows for data preparation, feature engineering, model training, evaluation, deployment, and inference.
Collaborate with data scientists and data engineers to transition experimental models into production-ready solutions.
Build and manage feature engineering and data pipelines supporting model retraining, scoring, monitoring, and downstream consumption.
Establish and maintain model lifecycle management processes using MLflow and Unity Catalog.
Manage model registration, versioning, lineage, experiment tracking, and controlled promotion across environments.
Develop automated testing, validation, and monitoring processes to improve reliability and reduce deployment risk.
Manage Databricks jobs, workflows, orchestration processes, and scheduled executions.
Support deployment patterns that enable operational use of AI/ML solutions in production environments.

Experience using Git-based development workflows and automated testing frameworks.
Strong understanding of data pipelines, feature engineering, batch processing, and workflow orchestration.
Experience supporting model development, deployment, and operational management.
Bachelors Degree

Experience supporting manufacturing, industrial IoT, quality engineering, or plant-floor analytics initiatives.
Experience with model governance, lineage tracking, reproducibility, and controlled model promotion processes.
Familiarity with model monitoring, operational observability, and validation frameworks.
Experience transitioning proof-of-concept or research-based models into production-ready solutions.
Package, version, and promote model artifacts with full traceability to source code, datasets, and registry versions.
Contribute to the development of reusable MLOps frameworks and deployment standards across multiple AI/ML initiatives.
Bachelors degree, Masters degree, or equivalent experience in Computer Science, Data Science, Engineering, or a related technical field.
Strong software engineering experience using Python.

Build and operationalize machine learning pipelines within Databricks to support model training, validation, batch scoring, and deployment workflows.
Implement and maintain CI/CD pipelines for machine learning code, data pipelines, and model promotion processes using Git-based development practices.
Collaborate with machine learning, data engineering, cloud platform, and business stakeholders to ensure scalable and supportable solutions.

This listing is sourced directly from Compunnel Inc.'s careers page and normalized into a canonical job model.