Remote ML Ops Engineer — Production ML/AI Systems

Slalom; Portland (ME); Hybrid; USD 110,208 - 137,760; Full time

Benefits offered by this job

401(k) with match

Health, dental, vision coverage

Well-being reimbursement

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 highly regulated, enterprise environment. You will transform validated models into scalable, governed systems, and own end-to-end lifecycle with CI/CD and Azure Databricks.

The role emphasizes hands-on ML engineering, MLOps, API-based deployment, and collaboration with data scientists and engineers to deliver reliable AI at scale.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, Data Science, or a related quantitative discipline.
• 5+ years of hands-on experience in Machine Learning Engineering, MLOps, or related software engineering roles supporting production AI systems.
• Demonstrated experience deploying and operating machine learning solutions in enterprise environments.
• Strong Python development skills and proficiency with machine learning frameworks such as Scikit-learn, PyTorch, and TensorFlow.

Responsibilities

• Design, build, and deploy production-grade machine learning and Generative AI solutions that solve complex business challenges.
• Own the end-to-end machine learning production lifecycle, including data ingestion, feature engineering, model deployment, monitoring, and lifecycle management.
• Develop, maintain, and optimize MLOps pipelines using Azure Databricks, MLflow, Unity Catalog, and automated CI/CD processes.
• Implement scalable model-serving architectures, including real-time APIs, batch inference pipelines, and feature stores.
• Convert data science prototypes and experimental notebooks into maintainable, production-ready software solutions.
• Collaborate with data engineering teams to ensure data pipelines, streaming architectures, and feature management platforms meet performance and quality requirements.
• Establish and maintain best practices for model versioning, reproducibility, deployment automation, monitoring, drift detection, A/B testing, and automated retraining.
• Build and manage online and batch model-serving endpoints, compute infrastructure, monitoring frameworks, and performance dashboards.
• Ensure compliance with data governance, privacy, security, and responsible AI standards.
• Communicate technical decisions, architecture patterns, and trade-offs effectively to both technical and non-technical stakeholders.

Skills

Python

Scikit-learn

PyTorch

TensorFlow

MLOps

APIs

Azure

CI/CD

GitHub Actions

Education

Bachelor’s or Master’s degree in CS/Software/Math/Data Science

Tools

Azure Databricks

MLflow

Docker

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 and Generative AI solutions in a highly regulated, enterprise environment. You will transform validated models into scalable, governed systems, and own end-to-end lifecycle with CI/CD and Azure Databricks.

The role emphasizes hands-on ML engineering, MLOps, API-based deployment, and collaboration with data scientists and engineers to deliver reliable AI at scale.