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Microsoft Machine Learning Jobs in Washington (NOW HIRING)

Microsoft

Senior Software Engineer- CTJ - Poly

Reston, VA · On-site

$127.40K - $168K/yr

We build foundational services that power Azure Machine Learning, Azure AI Services, Azure OpenAI, and Microsoft Foundry capabilities across air gapped, sovereign, and commercial clouds. Our team ...

Deloitte

AI Solutions Leader

Mclean, VA · On-site

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

DMI

Mid-Level Data Scientist

Washington, DC · On-site

The Mid-Level Data Scientist will build, train, and deploy machine learning models and AI-driven ... Microsoft Fabric and Apache Spark • Produce written documentation of model methodologies ...

DMI Computer

Mid-Level Data Scientist

Washington, DC · On-site

The Mid-Level Data Scientist builds, trains, and deploys machine learning models and AI-driven ... Microsoft Fabric and Apache Spark • Produce written documentation of model methodologies ...

New

Zantech

RPA/ML Solutions Architect

Camp Springs, MD · On-site +1

$66 - $87/hr

Certifications (Recommended) * RPA Platform Advanced Developer certification from UiPath, Automation Anywhere, Blue Prism, or Microsoft Power Automate * AWS Certified Machine Learning - Specialty ...

Zantech

RPA/ML Solutions Architect (Remote)

Camp Springs, MD · Remote

$64.50 - $85/hr

Certifications (Recommended) * RPA Platform Advanced Developer certification from UiPath, Automation Anywhere, Blue Prism, or Microsoft Power Automate * AWS Certified Machine Learning - Specialty ...

Zantech

RPA/ML Solutions Architect

Camp Springs, MD · On-site

$66 - $87/hr

Certifications (Recommended) * RPA Platform Advanced Developer certification from UiPath, Automation Anywhere, Blue Prism, or Microsoft Power Automate * AWS Certified Machine Learning - Specialty ...

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$48.2K

$99.7K

How much do microsoft machine learning jobs pay per year?

As of May 29, 2026, the average yearly pay for microsoft machine learning in Washington is $48,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,800.00 and $52,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Microsoft Machine Learning Engineer, and why are they important?

To thrive as a Microsoft Machine Learning Engineer, you need a solid background in computer science, mathematics, and statistics, typically supported by a relevant degree and experience in machine learning model development. Proficiency with tools such as Azure Machine Learning, Python, TensorFlow or PyTorch, and familiarity with cloud computing platforms is expected, along with certifications like Microsoft Certified: Azure AI Engineer Associate. Strong problem-solving skills, collaboration, and effective communication are crucial soft skills for successful project delivery and stakeholder engagement. These skills and qualities are vital for developing robust, scalable ML solutions that meet business objectives in dynamic environments.

What types of projects do Microsoft Machine Learning engineers typically work on, and how does collaboration with other teams factor into their daily responsibilities?

Microsoft Machine Learning engineers often work on projects involving large-scale data analysis, building predictive models, and developing AI-powered features for Microsoft products and services. Collaboration is a key part of the role; engineers frequently partner with data scientists, software developers, and product managers to align machine learning solutions with business objectives and user needs. Regular cross-functional meetings, code reviews, and joint problem-solving sessions are common, fostering a collaborative and innovative work environment. This teamwork not only enhances project outcomes but also provides valuable learning opportunities across different disciplines.

What is a Microsoft Machine Learning Engineer?

A Microsoft Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models using Microsoft technologies such as Azure Machine Learning, Python, and various data science tools. They work with large datasets to develop predictive models, automate processes, and provide data-driven insights for businesses. Their responsibilities often include data preprocessing, model training, evaluation, and deploying solutions to the cloud. They collaborate closely with data engineers, data scientists, and software developers to integrate machine learning solutions into applications. Proficiency in Microsoft Azure and knowledge of AI frameworks are essential for this role.
What are popular job titles related to Microsoft Machine Learning jobs in Washington? For Microsoft Machine Learning jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Microsoft Machine Learning jobs in Washington look for? The top searched job categories for Microsoft Machine Learning jobs in Washington are:
Microsoft Machine Learning jobs near you
Infographic showing various Microsoft Machine Learning job openings in Washington as of May 2026, with employment types broken down into 2% Internship, 3% As Needed, 70% Full Time, 23% Part Time, and 2% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $48,230 per year, or $23.2 per hour.
Senior AI / Machine Learning Engineer (Public Trust)

Senior AI / Machine Learning Engineer (Public Trust)

Praescient Analytics

Bethesda, MD • On-site

$111.80K - $153.60K/yr

Full-time

Retirement, PTO

Posted 3 days ago

Job description

Location: Bethesda, MD (Hybrid)
Clearance: Public Trust (Role may require additional background investigations)
Employment Type: Full-Time
US Citizenship is Required
Position Overview:
Praescient Analytics is seeking a highly experienced Senior AI/ML Engineer to support a mission-critical federal analytics and artificial intelligence modernization program. This role is responsible for designing, engineering, deploying, and operating production-grade AI and machine learning systems that support real-time decision-making, advanced analytics, and public safety outcomes.
The Senior AI/ML Engineer owns the end-to-end machine learning lifecycle, from data ingestion and model development through deployment, monitoring, and governance. This position plays a key role in operationalizing advanced analytics, building scalable MLOps pipelines, and integrating AI capabilities into cloud-native systems within a highly regulated federal environment.
Key Responsibilities:
  • Design, develop, train, and optimize machine learning and deep learning models supporting predictive analytics, classification, anomaly detection, NLP, and AI-assisted decision support.
  • Apply advanced ML techniques using supervised, unsupervised, and semi-supervised learning approaches.
  • Design and implement end-to-end MLOps pipelines supporting model training, validation, versioning, deployment, and rollback.
  • Deploy models into production environments using Microsoft Azure ML, containerization, and CI/CD pipelines.
  • Implement model monitoring, performance tracking, and drift detection to ensure long-term reliability and accuracy.
  • Build and maintain AI solutions leveraging Microsoft Azure services, including:
    • Azure Machine Learning
    • Azure Data Lake Storage
    • Azure Synapse Analytics
  • Integrate AI/ML solutions with existing data platforms, APIs, and analytics services.
  • Optimize AI workloads for cost, performance, and reliability in cloud environments.
  • Ensure AI systems adhere to federal standards for responsible AI, transparency, explainability, and auditability.
  • Support model documentation, validation artifacts, and compliance reporting.
  • Collaborate with governance and stakeholder teams to ensure models are suitable for high-impact decision-making.
  • Work closely with data scientists, data engineers, analysts, architects, and Agile project managers in a fast-paced Agile delivery environment.
  • Mentor junior engineers and contribute to shared engineering standards and best practices.

Required Qualifications:
Experience
  • Minimum of 5+ years of experience designing, deploying, and operating production AI/ML systems.
  • Demonstrated experience moving models from research or prototype stages into production environments.
  • Proven experience supporting AI systems in mission-critical or regulated settings.
  • Bachelor's Degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field - or equivalent professional experience.
  • Experience supporting federal, public-sector, or other regulated environments.

Technical Skills
  • Expert proficiency in Python and AI/ML frameworks such as PyTorch and/or TensorFlow.
  • Strong experience with machine learning libraries including Scikit-learn, NumPy, and Pandas.
  • Hands-on experience with Microsoft Azure AI/ML services, particularly Azure Machine Learning.
  • Experience building CI/CD pipelines for ML workflows.
  • Familiarity with containerization (Docker) and model deployment patterns.
  • Experience with SQL and data integration for ML workloads.
  • Proficiency with Git-based version control and collaborative development.

Communication & Leadership
  • Strong written and verbal communication skills.
  • Ability to explain complex AI/ML concepts to technical and non-technical stakeholders.
  • Proven ability to lead technical efforts and collaborate across multidisciplinary teams.
Clearance: Minimum of a Public Trust (U.S. Citizenship is Required)
Preferred Qualifications:
  • Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Engineering, or a related field - or equivalent professional experience.
  • Familiarity with AI agents, vector databases, large language models (LLMs), or Copilot-style architectures.
  • Azure certifications (AI Engineer, Data Scientist, or related).
  • Experience with streaming or near-real-time AI pipelines.

What you can expect from us:
  • Real opportunity for career growth in an environment where your achievements will be celebrated
  • Constant collaboration with numerous teams to ensure client success
  • A team that respects and embraces your ideas and expertise
  • Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain
  • A workplace dedicated to supporting and bettering public safety and government agencies

Benefits:
  • Very competitive salary based on qualifications and experience
  • Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)
  • 401(k) with company match
  • Travel & performance incentives
  • 3 weeks paid time off (plus Federal Holidays)
  • $5K annual training allowance
  • $500 book allowance

Praescient Analytics is a Certified Woman-Owned Small Business (WOSB) with over a decade of expertise in advanced analytics, engineering, and DevOps, specializing in transforming complex data into actionable intelligence for informed decision-making. Since 2011, we have supported over 40 organizations across diverse domains, including military intelligence operations, financial and fraud investigations, and insider threat detection.
Our team of experts-skilled in cloud computing, artificial intelligence, machine learning, data science, DevOps, and engineering-brings deep experience in solving complex challenges. With a proven track record in federal contracting, we deliver tailored, high-impact solutions designed to enhance operational efficiency, ensure mission success, and address the evolving needs of our clients. Praescient's innovative and adaptive approach makes us a trusted partner in delivering data-driven insights and technological excellence for critical missions.
Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information.
US Citizenship Required
Interested Candidates: Please forward your resume to recruiting@praescientanalytics.com and please visit our website to apply online at www.praescientanalytics.applicantstack.com/x/openings.

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