Remote ML Ops Engineer - Production AI (Project-Based)

Slalom; Richmond (VA); Hybrid; USD 228,681,600 - 286,540,800; Full time

Benefits offered by this job

401(k) match

Health coverage

Adoption assistance

Fertility assistance

Long-term disability

Well-being stipend

Job summary

Slalom, a global technology and business consulting firm, seeks an experienced AI/ML Engineer to design, deploy, and operate production-grade ML and Generative AI in a highly regulated enterprise setting. You will build scalable, governed AI systems and own the end-to-end lifecycle from data ingestion to monitoring.

You will work with data scientists, data engineers, and business stakeholders in agile teams, delivering reliable AI solutions on Azure Databricks, MLflow, and feature stores, with

Qualifications

• Bachelor’s or Master’s degree in CS, SE, Math, Stats, Data Science, or related quantitative field.
• 5+ years of hands-on experience in Machine Learning Engineering, MLOps, or related software engineering roles supporting production AI systems.
• Proven experience deploying and operating machine learning solutions in enterprise environments.
• Strong Python development skills and proficiency with ML frameworks such as Scikit-learn, PyTorch, and TensorFlow.
• Experience developing and deploying APIs and microservices using FastAPI, Flask, MLflow Model Serving.
• Experience deploying and supporting both front-end and back-end applications in Azure environments.
• Deep expertise with Azure Databricks, including Apache Spark, Delta Lake, Databricks, Unity Catalog, Feature Store, Cluster management and optimization
• Strong hands-on experience with MLflow for Experiment tracking, Model registry, Model packaging, and Automated deployment
• Experience implementing CI/CD pipelines using Azure DevOps and/or GitHub Actions.
• Strong knowledge of Git-based development workflows, branching strategies, and pull request processes.
• Experience building, packaging, and deploying containerized applications using Docker.
• Working knowledge of Azure cloud services, including Azure Data Lake Storage Gen2 (ADLS), Azure Key Vault, Azure Monitor, Cloud cost optimization practices
• Excellent communication, collaboration, and problem-solving skills.
• Ability to operate independently and lead technical delivery efforts within agile, cross-functional teams.

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

FastAPI

Flask

MLflow

Docker

Azure Databricks

Git

Spark

Delta Lake

Unity Catalog

CI/CD

Azure

Kubernetes

Education

Bachelor's or Master’s degree in CS/SE/Math/Stats/Data Science or related field

Tools

Azure DevOps

MLflow Model Serving

FastAPI

Flask

Docker

Azure Data Lake Storage Gen2

Job description

Slalom, a global technology and business consulting firm, seeks an experienced AI/ML Engineer to design, deploy, and operate production-grade ML and Generative AI in a highly regulated enterprise setting. You will build scalable, governed AI systems and own the end-to-end lifecycle from data ingestion to monitoring.

You will work with data scientists, data engineers, and business stakeholders in agile teams, delivering reliable AI solutions on Azure Databricks, MLflow, and feature stores, with