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Microsoft Machine Learning Jobs in Washington (NOW HIRING)

Ampcus Inc

System Analyst (AI/ML)

Woodbridge, VA · On-site

... machine learning frameworks, data visualizing frameworks and have experience in developing ML models and AI agents using Python, as well as being familiar with the Microsoft Azure environment.

New

CACI

Data Scientist

Alexandria, VA

The Data Scientist will leverage advanced analytics, machine learning, automation, and data fusion ... Strong proficiency with Microsoft Office Suite, including the ability to develop technical ...

CACI International, Inc.

Data Scientist

Alexandria, VA · On-site

The Data Scientist will leverage advanced analytics, machine learning, automation, and data fusion ... Strong proficiency with Microsoft Office Suite, including the ability to develop technical ...

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Microsoft Machine Learning information

See Washington salary details

$28.9K

$48.2K

$99.7K

How much do microsoft machine learning jobs pay per year?

As of Sep 14, 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 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 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 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 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 August 2026, with employment types broken down into 70% Full Time, 20% Part Time, and 10% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $48,230 per year, or $23.2 per hour.

Insights & Analytics Senior Specialist

Gaithersburg, MD • On-site

AstraZeneca
Pharmaceutical Product Wholesalers • 10K+ employees
Learn more about AstraZenecaexternal

$93K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted yesterday

AstraZeneca rating

8.4

Company rating: 8.4 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

Job description

Location: Gaithersburg, USA
Hybrid: 3 days a week onsite
Insights & Analytics Senior Specialist translates complex business and scientific challenges into practical, scalable machine learning solutions
The role contributes across the machine learning lifecycle, from understanding the problem and assessing the available data through to model development, deployment, monitoring, and continuous improvement. It requires the ability to make sound technical decisions, explain them clearly, and balance innovation with the expectations of a regulated and quality-focused environment.
Typical Accountabilities
  • Translate needs into solutions: Work with stakeholders to understand business or scientific problems, assess whether machine learning is an appropriate approach, and define clear objectives, success measures, and delivery plans.
  • Develop machine learning solutions: Design, build, evaluate, and improve models using appropriate statistical and machine learning techniques. This may include deep learning approaches for structured, text, image, or other unstructured data.
  • Work with advanced AI methods: Apply modern approaches such as natural language processing, generative AI and AI Agents/Workflows based on the problem being addressed. Select methods based on their suitability, performance, maintainability, and governance requirements.
  • Deliver production-ready capabilities: Work beyond experimentation to ensure that models can be packaged, deployed, integrated with relevant systems, monitored, and maintained over time. Contribute to the design of reliable and scalable AI architectures.
  • Use cloud and engineering practices: Develop and deploy solutions using cloud platforms such as AWS or Microsoft Azure, and use technologies such as Docker, source control, automated testing, and continuous integration and delivery to support consistent and reproducible delivery.
  • Maintain quality and governance: Define appropriate data and model quality criteria, validate results, document assumptions, and consider issues such as explainability, bias, privacy, security, performance degradation, and responsible use of AI.
  • Communicate with clarity: Present technical findings and recommendations in a way that is meaningful to both technical and non-technical audiences. Communicate model performance, uncertainty, limitations, and risks openly so stakeholders can make informed decisions.
  • Provide technical leadership: Contribute to technical design discussions, code and model reviews, reusable components, engineering standards, and communities of practice. Provide guidance and informal mentoring to colleagues where appropriate.
  • Operate as an individual contributor: Deliver work within agreed scope and priorities, influencing through technical expertise, collaboration, and sound judgement rather than through formal line management.
  • Work within the relevant country remit: Comply with applicable local policies, standards, regulatory expectations, and organizational requirements.

Qualifications and Skills
Essential
  • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Mathematics, Statistics, or a related discipline, or equivalent professional experience.
  • Typically at least five years of experience as a Data Scientist, Machine Learning Engineer, AI Engineer, or in a related role. Experience in healthcare, pharmaceuticals, life sciences, or another regulated and data-intensive environment is particularly relevant.
  • Demonstrated experience taking machine learning work from problem definition and data preparation through to model evaluation and, deployment or operational use.
  • Experience working with text, images, or other unstructured data, including relevant methods in natural language processing or computer vision. Understanding of modern deep learning architectures, including the role of attention mechanisms and transformer-based models.
  • Strong programming experience in Python, with the ability to write maintainable, tested, and reusable code. Experience working with databases, APIs, and data pipelines is also expected.
  • Experience using at least one major cloud platform, preferably AWS or Microsoft Azure, to develop, train, deploy, or operate machine learning solutions.
  • Experience with Docker and familiarity with software engineering and MLOps practices such as version control, testing, deployment automation, experiment tracking, monitoring, and model lifecycle management.

The annual base pay for this position ranges from $93,868.00 - $140,802.00 USD. Our positions offer eligibility for various incentives-an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles. Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans.
Are you ready to be part of a talented, cross-functional team working together to improve lives and make the biggest possible impact for patients, science and society?
Why AstraZeneca?
When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility.
Apply now!
Date Posted
08-Sept-2026
Closing Date
24-Sept-2026
Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.

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About AstraZeneca

Sourced by ZipRecruiter

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialization of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies. A place built on courage, curiosity and collaboration - we make bold decisions driven by patient outcomes. Empowered to lead at every level, free to ask questions and take smart risks that write the next chapter for our pipeline and Oncology team. Make a meaningful impact that brings real benefits to society. By applying your knowledge of data, you will help to redefine our industry and ultimately save lives. Work with experts who share a common goal: to accelerate the potential of medicines and the science of tomorrow.

Industry

Pharmaceutical product wholesalers and pharmaceutical and medicine manufacturing

Company size

10,000+ Employees

Headquarters location

Cambridge, Cambridgeshire, GB

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