Senior ML Ops Engineer — Remote Project Contract

Slalom; San Antonio (TX); Hybrid; USD 110,208 - 137,760; Full time

Benefits offered by this job

Healthcare coverage

401(k) with match

Well-being program

Job summary

Slalom is seeking an experienced AI/ML Engineer to design, deploy, and operate production-grade ML and Generative AI solutions in a regulated enterprise setting. You will transform validated models into scalable, governed production systems and collaborate with data scientists, data engineers, and business stakeholders to deliver reliable AI solutions.

The role emphasizes hands-on MLOps, model deployment, Azure Databricks, and cloud-native platforms within an agile team to tackle complex

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, Data Science, or related quantitative field.
• 5+ years of hands-on experience in Machine Learning Engineering, MLOps, or related software engineering roles.

Responsibilities

• Design, build, and deploy production-grade ML and Generative AI solutions.
• Own end-to-end ML production lifecycle: data ingestion, feature engineering, deployment, monitoring, lifecycle management.
• Develop and optimize MLOps pipelines with Azure Databricks, MLflow, Unity Catalog, CI/CD processes.
• Implement scalable model-serving architectures including real-time APIs and batch pipelines.
• Collaborate with data engineering to ensure performance and data quality across pipelines.
• Establish best practices for versioning, reproducibility, deployment automation, monitoring, and retraining.
• Build and manage endpoints, compute infra, monitoring dashboards.
• Ensure data governance, privacy, security, and responsible AI standards.

Skills

Python development

ML frameworks

API / microservices

Azure Databricks

CI/CD pipelines

Docker

Education

Bachelor’s or Master’s in CS/SE/Math/Data Science

Tools

MLflow

GitHub Actions

Azure DevOps

Databricks tooling

Job description

Slalom is seeking an experienced AI/ML Engineer to design, deploy, and operate production-grade ML and Generative AI solutions in a regulated enterprise setting. You will transform validated models into scalable, governed production systems and collaborate with data scientists, data engineers, and business stakeholders to deliver reliable AI solutions.

The role emphasizes hands-on MLOps, model deployment, Azure Databricks, and cloud-native platforms within an agile team to tackle complex