Remote Project-Based ML Ops Engineer for Production AI

Slalom; Milwaukee (WI); Ibrido; USD 110.208 - 137.760; Tempo pieno

Vantaggi offerti da questo lavoro

401(k) with match

Health, dental, & vision coverage

Adoption and fertility assistance

Long-term disability

$350 wellbeing reimbursement

Descrizione del lavoro

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. This role emphasizes MLOps, model deployment, Azure Databricks, and cloud-native platforms, working with data scientists, data engineers, and business stakeholders to deliver reliable AI solutions.

You will own end-to-end ML production lifecycle, ensure governance, monitoring, and scalable model serving, with a focus

Competenze

• 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.
• Experience developing and deploying APIs and microservices using frameworks such as: 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.

Mansioni

• 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.

Conoscenze

Python development

Machine Learning

MLOps

Communication

Agile collaboration

APIs

Git workflows

Problem solving

Formazione

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

Strumenti

Azure Databricks

MLflow

Unity Catalog

Delta Lake

Docker

FastAPI/Flask

Descrizione del lavoro

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. This role emphasizes MLOps, model deployment, Azure Databricks, and cloud-native platforms, working with data scientists, data engineers, and business stakeholders to deliver reliable AI solutions.

You will own end-to-end ML production lifecycle, ensure governance, monitoring, and scalable model serving, with a focus