Remote ML Ops Engineer (Contract) for Generative AI Production

Slalom; Austin (TX); Hybrid; USD 110,208 - 137,760; Full time

Benefits offered by this job

401(k) match

Health/dental/vision coverage

Adoption assistance

Fertility assistance

Long-term disability

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 own end-to-end ML production lifecycle, collaborate with data scientists, data engineers, and stakeholders, and transform validated models into scalable, governed systems that deliver critical business outcomes.

Qualifications

• Bachelor’s or Master’s degree in CS, SE, Math, Stats, Data Science, or 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 Scikit-learn, PyTorch, and TensorFlow.
• Experience developing and deploying APIs and microservices using FastAPI, Flask, MLflow Model Serving.
• Experience deploying and supporting Azure Databricks, including Spark, Delta Lake, Unity Catalog, Feature Store, and cluster management.
• Experience implementing CI/CD pipelines using Azure DevOps and/or GitHub Actions.
• Strong knowledge of Git-based development workflows and containerization with Docker.
• Working knowledge of Azure services (ADLS Gen2, Key Vault, Monitor) and cost optimization practices.

Responsibilities

• Design, build, and deploy production-grade ML and Generative AI solutions for enterprise challenges.
• Own end-to-end ML production lifecycle: data ingestion, feature engineering, deployment, monitoring, lifecycle management.
• Develop, maintain, and optimize MLOps pipelines with Azure Databricks, MLflow, Unity Catalog, and CI/CD processes.
• Implement scalable model-serving architectures with real-time APIs and batch inference pipelines.
• Transform data science prototypes into production-ready software.
• Collaborate with data engineering to ensure data pipelines meet performance and quality targets.
• Establish model versioning, reproducibility, deployment automation, monitoring, drift detection, and automated retraining.
• Build online and batch model-serving endpoints and dashboards for performance.
• Ensure compliance with data governance, privacy, security, and responsible AI standards.
• Communicate decisions and trade-offs to both technical and non-technical stakeholders.

Skills

Python

Scikit-learn

PyTorch

TensorFlow

MLOps

Azure Databricks

API development

Docker

CI/CD

Azure DevOps

GitHub Actions

Spark

Unity Catalog

Education

Bachelor’s or Master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, Data Science, or related

Tools

MLflow Model Serving

FastAPI

Flask

MLflow

Docker

Azure Databricks

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 own end-to-end ML production lifecycle, collaborate with data scientists, data engineers, and stakeholders, and transform validated models into scalable, governed systems that deliver critical business outcomes.