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Microsoft Machine Learning Engineer Jobs (NOW HIRING)

Prosum Inc.

Machine Learning Engineer

CA · On-site

$75 - $89/hr

Machine Learning Engineer Pay Rate: $75-$89/hour Position Summary We are seeking a skilled Machine Learning Engineer (MLOps) to support the full lifecycle of machine learning models, including design ...

Spotify

Machine Learning Engineer

They are seeking a Machine Learning Engineer to build systems that analyze the performance of music promotions, providing actionable insights for creators and partners. Responsibilities : • ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Spotify

Machine Learning Engineer

Spotify is a leading music streaming platform, and they are seeking a Machine Learning Engineer to join their Music Promotion team. The role involves building systems to understand the performance of ...

Eccalon LLC

Machine Learning Engineer

Detroit, MI · On-site

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Samprasoft

Machine Learning Engineer

Mclean, VA

GCP/AWS Machine Learning Engineer Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for ...

DocuSign

Machine Learning Engineer

Seattle, WA · On-site

Machine Learning Engineer As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent ...

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All JobsMicrosoft Machine Learning Engineer Jobs

Microsoft Machine Learning Engineer information

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$31.5K

$128.8K

$193.5K

How much do microsoft machine learning engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for microsoft machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is the difference between Microsoft Machine Learning Engineer vs Data Scientist?

AspectMicrosoft Machine Learning EngineerData Scientist
Required CredentialsTypically requires a degree in Computer Science, Data Science, or related fields; certifications like Azure Data Scientist Associate are commonUsually holds a degree in Statistics, Mathematics, or Data Science; certifications like Certified Data Scientist are beneficial
Work EnvironmentFocuses on developing, deploying, and maintaining machine learning models within Microsoft Azure and related platformsAnalyzes data, builds statistical models, and provides insights across various tools and programming languages
Employer & Industry UsagePrimarily employed by tech companies, especially those using Microsoft Azure; roles are common in AI and cloud servicesFound across industries like finance, healthcare, and tech; roles involve data analysis and predictive modeling

While both roles involve working with data and models, Microsoft Machine Learning Engineers focus on deploying machine learning solutions within Azure, whereas Data Scientists primarily analyze data and develop insights using various tools. The roles often overlap but differ in their core responsibilities and technical focus.

What cities are hiring for Microsoft Machine Learning Engineer jobs? Cities with the most Microsoft Machine Learning Engineer job openings:
Machine Learning Engineer

Machine Learning Engineer

Prosum Inc.

CA • On-site

$75 - $89/hr

Contractor

Posted 4 days ago

Job description

Job Description
Machine Learning Engineer
Pay Rate: $75-$89/hour
Position Summary
We are seeking a skilled Machine Learning Engineer (MLOps) to support the full lifecycle of machine learning models, including design, development, deployment, and maintenance. This role focuses on building scalable, production-ready AI/ML solutions and ensuring seamless integration within existing systems.
The ideal candidate will collaborate with cross-functional teams to deploy, monitor, and optimize machine learning models that drive operational efficiency, innovation, and data-driven decision-making. This position requires strong experience in MLOps, DevOps practices, and cloud-based AI infrastructure.
Key Responsibilities
  • Design, build, deploy, and maintain machine learning models in production environments
  • Develop and manage end-to-end MLOps pipelines, including model versioning, monitoring, and automation
  • Implement scalable ML infrastructure using cloud platforms (AWS, Azure, or GCP)
  • Build and optimize CI/CD pipelines for automated testing and deployment of ML models
  • Collaborate with data scientists, data engineers, and DevOps teams to operationalize AI solutions
  • Monitor model performance, system health, and data drift; implement logging and alerting solutions
  • Ensure reliability, scalability, and performance of ML systems in real-time inference environments
  • Maintain version control for models and code to support reproducibility and collaboration
  • Apply best practices for testing, debugging, and performance optimization
  • Ensure compliance with data security, privacy, and regulatory standards
  • Create and maintain technical documentation for ML systems and processes
Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, or a related field
  • 3+ years of experience in machine learning engineering or MLOps
  • Hands-on experience managing the end-to-end machine learning lifecycle
  • Strong programming skills in Python, R, and/or SQL
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
  • Experience with containerization (Docker) and orchestration tools (Kubernetes)
  • Experience with infrastructure as code tools such as Terraform
  • Experience building and maintaining CI/CD pipelines (e.g., GitHub Actions)
  • Strong understanding of software development, system architecture, and deployment processes
  • Experience with monitoring, logging, and performance tuning of ML systems
  • Knowledge of version control systems (e.g., Git)
Preferred Qualifications
  • Master's degree in Computer Science, Engineering, or a related field
  • Experience working with healthcare data or regulated environments
  • Familiarity with Electronic Health Record (EHR) systems
  • Experience with predictive modeling, natural language processing (NLP), and large language models (LLMs)
  • Knowledge of retrieval-augmented generation (RAG) frameworks and their applications
  • Understanding of agile methodologies and DevOps lifecycle practices
Core Competencies
  • Production-grade ML model deployment and lifecycle management
  • Scalable infrastructure design for AI/ML workloads
  • Cross-functional collaboration and technical leadership
  • Strong analytical and problem-solving skills
  • Effective technical communication and documentation

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