Remote ML Ops Engineer (Project-Based)

Slalom; Minneapolis (MN); Hybrid; USD 110,208 - 137,760; Full time

Benefits offered by this job

401(k) match

Health insurance

Well-being reimbursement

Job summary

Slalom is seeking an experienced AI/ML Engineer to design, deploy, and operate production-grade machine learning solutions in a regulated enterprise environment. This remote/hybrid consultant role focuses on MLOps, model deployment, Azure Databricks, and scalable AI platforms.

You will lead end-to-end ML production lifecycles, collaborate with data scientists and engineers, implement CI/CD pipelines, and ensure governance, security, and compliant AI practices across enterprise projects.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, Data Science, or related quantitative discipline.

Responsibilities

• Design, build, and deploy production-grade ML/Generative AI solutions.
• Own end-to-end ML production lifecycle: data ingestion, feature engineering, deployment, monitoring, lifecycle management.
• Develop and optimize MLOps pipelines using Azure Databricks, MLflow, Unity Catalog, and CI/CD processes.
• Implement scalable model-serving architectures with real-time APIs and batch inference pipelines.
• Convert prototypes into production-ready software solutions.
• Collaborate with data engineering to ensure robust data pipelines and feature management.
• Establish model governance, reproducibility, deployment automation, monitoring, drift detection, A/B testing, retraining.
• Build online and batch model-serving endpoints and compute infrastructure.

Skills

Python

ML frameworks

APIs & microservices

Azure Databricks

Docker

CI/CD

Git workflows

Containerization

Spark

Delta Lake

Education

Bachelor’s or Master’s degree in a quantitative field

Tools

MLflow

Azure DevOps

GitHub Actions

FastAPI

Flask

Job description

Slalom is seeking an experienced AI/ML Engineer to design, deploy, and operate production-grade machine learning solutions in a regulated enterprise environment. This remote/hybrid consultant role focuses on MLOps, model deployment, Azure Databricks, and scalable AI platforms.

You will lead end-to-end ML production lifecycles, collaborate with data scientists and engineers, implement CI/CD pipelines, and ensure governance, security, and compliant AI practices across enterprise projects.