Remote ML Ops Engineer - Project-Based Contract

Slalom

Birmingham (AL)

Hybrid

USD 110,208 - 137,760

Full time

14 days+

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Benefits offered by this job

401(k) with match

Health, dental, vision coverage

Paid holidays & time off

Well-being reimbursement $350

Job summary

Slalom is seeking an experienced AI/ML Engineer to design, deploy, and operate production-grade machine learning and Generative AI solutions in a regulated enterprise environment. You will transform validated models into scalable, governed systems and drive critical business outcomes.

The role emphasizes hands-on MLOps, model deployment, Azure Databricks, and cloud-native platforms. You will work with data scientists, data engineers, and stakeholders in agile teams to deliver reliable AI

Qualifications

Bachelor’s or Master’s degree in a quantitative field.
5+ years in Machine Learning Engineering, MLOps or related software roles.
Experience deploying and operating machine learning solutions in enterprise environments.
Strong Python and ML framework experience (scikit-learn, PyTorch, TensorFlow).
Experience developing APIs and microservices (FastAPI, Flask, MLflow Model Serving).
Experience deploying in Azure environments and Azure Databricks.
Knowledge of MLflow for experiment tracking and model registry.
CI/CD pipelines with Azure DevOps or GitHub Actions.

Responsibilities

Design, build, and deploy production-grade ML and Generative AI solutions.
Own end-to-end ML production lifecycle (data ingest, feature engineering, deployment, monitoring).
Develop and optimize MLOps pipelines using Azure Databricks, MLflow, Unity Catalog.
Implement scalable model-serving architectures (real-time APIs, batch inference, feature stores).
Convert prototypes into production-ready software and maintain them.
Collaborate with data engineers to ensure robust data pipelines and quality.