Remote ML Ops Engineer - Production AI Solutions

Slalom; Detroit (MI); Hybrid; USD 110,208 - 137,760; Full time

Benefits offered by this job

401(k) with match

Health, dental, vision coverage

Fertility and adoption assistance

Well-being reimbursement

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 environment. You will transform validated models into scalable, governed production systems.

You will work with data scientists and engineers in an agile setting, focusing on MLOps, deployment, monitoring, and secure, governed AI at scale. This role offers remote/hybrid engagement via consulting projects.

Qualifications

• Bachelor’s or Master’s in CS or related quantitative field.
• 5+ years in ML engineering/production AI.
• Proven deployment/operation of ML in enterprise environments.
• Strong Python and ML frameworks proficiency (PyTorch, TensorFlow, Scikit-learn).

Responsibilities

• Design and deploy production-grade ML and Generative AI solutions.
• Own end-to-end ML production lifecycle (data ingest, features, deployment, monitoring).
• Develop and optimize MLOps pipelines on Azure Databricks, MLflow, and Unity Catalog.
• Implement scalable model-serving architectures (real-time APIs, batch inference).
• Collaborate with data engineers to ensure robust data pipelines and quality.
• Maintain model governance, monitoring, drift detection, and retraining processes.
• Communicate decisions and trade-offs to technical and non-technical stakeholders.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

MLOps

CI/CD

APIs

Docker

Azure Databricks

Education

Bachelor's or Master's in CS

Tools

MLflow

FastAPI

Flask

GitHub Actions

Docker

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 environment. You will transform validated models into scalable, governed production systems.

You will work with data scientists and engineers in an agile setting, focusing on MLOps, deployment, monitoring, and secure, governed AI at scale. This role offers remote/hybrid engagement via consulting projects.