Remote ML Ops Engineer (Contract) – Enterprise AI Deployments

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

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’ll own the end-to-end ML production lifecycle, collaborate with data scientists, data engineers, and business stakeholders, and advance MLOps pipelines using Azure Databricks, MLflow, and CI/CD processes across hybrid, client-facing engagements.

Qualifications

• 5+ years of hands-on experience in Machine Learning Engineering or MLOps.
• Experience deploying and operating ML solutions in enterprise environments.
• Strong Python development skills with Scikit-learn, PyTorch, and TensorFlow.
• Experience developing and deploying APIs and microservices with FastAPI, Flask, and MLflow Serving.
• Experience deploying front-end and back-end apps in Azure.
• Deep expertise with Azure Databricks, including Spark, Delta Lake, Unity Catalog, and Feature Store.
• Experience CI/CD using Azure DevOps or GitHub Actions.
• Git-based workflows, branching, PR processes.
• Containerized apps with Docker.
• Working knowledge of Azure services including ADLS, Key Vault, Monitor.

Responsibilities

• Design, build, and deploy production‑grade ML and Generative AI solutions.
• Own the end‑to‑end ML production lifecycle including data ingestion and feature engineering.
• Develop and optimize MLOps pipelines using Azure Databricks, MLflow, and CI/CD.
• Implement scalable model‑serving architectures (real-time APIs, batch inference).
• Convert prototypes into production software solutions.
• Collaborate with data engineering to ensure scalable data pipelines and feature management.
• Establish best practices for model versioning, deployment automation, monitoring, and retraining.
• Build online and batch model-serving endpoints and dashboards.
• Ensure compliance with data governance and responsible AI standards.
• Communicate decisions and architecture to technical and non‑technical stakeholders.

Skills

Python

Scikit-learn

PyTorch

TensorFlow

APIs & Microservices

FastAPI

Flask

MLflow

Azure Databricks

Education

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

Tools

Docker

MLflow

Apache Spark

Delta Lake

Unity Catalog

Feature Store

CI/CD (Azure DevOps/GitHub Actions)

Git

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’ll own the end-to-end ML production lifecycle, collaborate with data scientists, data engineers, and business stakeholders, and advance MLOps pipelines using Azure Databricks, MLflow, and CI/CD processes across hybrid, client-facing engagements.