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Azure Ml Jobs in Virginia (NOW HIRING)

Deploy and maintain models on Azure (Azure ML, Azure Databricks, and/or AKS), ensuring reliability and cost efficiency at scale. * Monitor model performance in production, diagnose drift and ...

Deploy and maintain models on Azure (Azure ML, Azure Databricks, and/or AKS), ensuring reliability and cost efficiency at scale.Monitor model performance in production, diagnose drift and degradation ...

AI/ML Engineer, Lead

Ashburn, VA

$104K - $138K/yr

Experience with cloud platforms, such as AWS, Azure, or GCP, and tools for scalable ML systems, such as SageMaker, Azure ML, or Vertex AI * Experience building data pipelines * Experience with MLOps ...

AI/ML Engineer, Lead

Ashburn, VA · On-site

$104K - $138K/yr

Experience with cloud platforms, such as AWS, Azure, or GCP, and tools for scalable ML systems, such as SageMaker, Azure ML, or Vertex AI * Experience building data pipelines * Experience with MLOps ...

AI/ML Engineer, Lead

Ashburn, VA · On-site +1

$104K - $138K/yr

Experience with cloud platforms, such as AWS, Azure, or GCP, and tools for scalable ML systems, such as SageMaker, Azure ML, or Vertex AI * Experience building data pipelines * Experience with MLOps ...

AI/ML Engineer, Lead

Ashburn, VA · On-site

$129 - $292/hr

Experience with cloud platforms, such as AWS, Azure, or GCP, and tools for scalable ML systems, such as SageMaker, Azure ML, or Vertex AI* Experience building data pipelines* Experience with MLOps ...

Lead AI/ML Engineer

Ashburn, VA · On-site

$104K - $138K/yr

Experience with cloud platforms, such as AWS, Azure, or Google Cloud Platform, and tools for scalable ML systems, such as SageMaker, Azure ML, or Vertex AI * Experience building data pipelines

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Azure Ml information

See Virginia salary details

$10

$57

$79

How much do azure ml jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for azure ml in Virginia is $57.90, according to ZipRecruiter salary data. Most workers in this role earn between $52.45 and $65.05 per hour, depending on experience, location, and employer.

What is an Azure ML?

An Azure ML job refers to a machine learning task executed within Microsoft Azure Machine Learning, a cloud-based platform for building, training, and deploying ML models. Jobs can include data preprocessing, model training, hyperparameter tuning, and inference deployment. Users can run jobs using compute resources such as Azure Machine Learning compute clusters or virtual machines. Jobs are typically orchestrated using Azure ML Pipelines, SDKs, or Studio for automation and reproducibility.

What does an Azure ML do?

Professionals in Azure ML roles are typically responsible for designing and deploying machine learning models, pre-processing and analyzing large datasets, and monitoring model performance in Azure’s cloud environment. Daily tasks often include writing and optimizing code, integrating services and APIs, automating ML pipelines, and collaborating closely with data scientists, engineers, and business analysts. You may also be involved in troubleshooting production issues, conducting research to improve algorithms, and documenting your workflows. This role requires adaptability and good organizational skills to manage multiple projects in a dynamic, team-oriented setting.

What are the key skills and qualifications needed to thrive in the Azure ML position?

To thrive as an Azure ML professional, you need a strong background in machine learning, data science, and programming (commonly Python or R), often supported by a relevant degree or certifications such as Microsoft Certified: Azure AI Engineer Associate. Experience with Azure Machine Learning Studio, cloud computing environments, workflow orchestration, and automation tools is essential. Effective communication, problem-solving abilities, and a collaborative mindset further distinguish top candidates. These skills are crucial to successfully designing, deploying, and managing scalable AI solutions on Azure's cloud platform while working effectively with data teams and stakeholders.

Infographic showing various Azure Ml job openings in Virginia as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $120,434 per year, or $57.9 per hour.

Testing not a real job 1

SiloSmashers

Alexandria, VA • On-site

Full-time

Re-posted 9 days ago


Job description

About the Role

We're looking for a Senior ML Engineer to join a product team and help build, train, and ship machine learning models that power real user-facing features. This is a hands-on role for someone who enjoys owning the full lifecycle of a model - from experimentation through production deployment and monitoring - and who is comfortable working closely with product and engineering partners in a hybrid office environment.

What You'll Do
  • Design, build, and train machine learning models to solve product problems, iterating from prototype to production.
  • Own the MLOps lifecycle: experiment tracking, reproducible training pipelines, model versioning, deployment, and monitoring.
  • Partner directly with product managers and engineers embedded in your team to translate business requirements into ML solutions.
  • Deploy and maintain models on Azure (Azure ML, Azure Databricks, and/or AKS), ensuring reliability and cost efficiency at scale.
  • Monitor model performance in production, diagnose drift and degradation, and drive retraining and improvement cycles.
  • Write clean, well-tested, production-grade Python code and contribute to shared ML tooling and best practices.
  • Collaborate cross-functionally to define success metrics, run experiments (A/B tests), and communicate results to technical and non-technical stakeholders.
What We're Looking For
  • 6–10 years of professional experience in software/ML engineering, with a strong track record of building and training ML models.
  • Deep hands-on expertise in Python and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
  • Practical MLOps experience - tools such as MLflow, Kubeflow, or Airflow for pipelines, tracking, and deployment.
  • Required: Certified Azure experience (e.g., Microsoft Certified: Azure AI Engineer Associate / AI-102), plus hands-on production experience with Azure ML, Azure Databricks, or AKS.
  • Solid understanding of the full ML lifecycle: data preparation, training, evaluation, deployment, and monitoring.
  • Strong communication skills and comfort working embedded within a cross-functional product team.
  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Nice to Have
  • Experience with large language models (LLMs) or generative AI APIs (e.g., Claude, OpenAI, Azure OpenAI Service).