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Junior Aws Machine Learning Jobs in Washington (NOW HIRING)

Hirekeyz Inc

Sr. Machine Learning Engineer

Fort Belvoir, VA · On-site

$118K - $162K/yr

Role: Sr. Machine Learning Engineer Location: Ft. Belvoir, VA (On-site with Hybrid Option) Duration ... S. Army Command to create cybersecurity solutions working with cloud-based architecture (AWS ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

Experience training and serving models in cloud environments (AWS, Azure, GCP) * Proficiency with ... Strong fundamentals in machine learning including model architecture design, training strategies ...

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Junior Aws Machine Learning information

What is a junior AWS machine learning engineer?

Junior AWS Machine Learning engineers are entry-level professionals who work with Amazon Web Services (AWS) to develop, deploy, and maintain machine learning models. They assist in data preparation, model training, and integration of AI solutions using AWS tools such as SageMaker, Lambda, and S3. These engineers often collaborate with data scientists and software teams to implement predictive analytics and automation solutions on the AWS cloud platform. Their role typically involves learning best practices for cloud security, data handling, and scalable machine learning deployment.

What are the key skills and qualifications needed to thrive as a junior AWS machine learning engineer?

To thrive as a Junior AWS Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of machine learning concepts, and a relevant degree in computer science or a related field. Familiarity with AWS services like SageMaker, Lambda, and S3, as well as certifications such as AWS Certified Machine Learning – Specialty, are highly valuable. Strong problem-solving skills, attention to detail, and the ability to communicate technical ideas clearly help you stand out in this role. These skills and qualities are crucial for efficiently developing, deploying, and maintaining machine learning solutions on AWS in collaborative, fast-paced environments.

What are some common challenges faced by junior AWS machine learning engineers when deploying models to production environments?

Junior AWS Machine Learning Engineers often encounter challenges such as managing the scalability of their models, ensuring data security and compliance in the cloud, and integrating machine learning pipelines with existing AWS services. Since production environments require high reliability, newcomers may also need to learn how to monitor model performance and troubleshoot issues using AWS tools like SageMaker and CloudWatch. Collaborating closely with data engineers and DevOps teams is essential to streamline deployment and maintain model accuracy over time.

What is the difference between Junior Aws Machine Learning vs Data Scientist?

AspectJunior Aws Machine LearningData Scientist
Required CredentialsBasic AWS certifications, entry-level ML knowledgeAdvanced degrees, certifications like AWS, data analysis skills
Work EnvironmentCloud platforms, machine learning projects, collaborative teamsData analysis, modeling, research, cross-functional teams
Employer & Industry UsageTech companies, startups, cloud service providersFinance, healthcare, tech, research institutions

Junior AWS Machine Learning roles focus on implementing ML models using AWS tools with foundational knowledge, while Data Scientists typically handle broader data analysis, modeling, and research tasks. The roles overlap in cloud-based ML work but differ in scope and experience level.

What are the most commonly searched types of Aws Machine Learning jobs in Washington?

The most popular types of Aws Machine Learning jobs in Washington are:

What are popular job titles related to Junior Aws Machine Learning jobs in Washington?

For Junior Aws Machine Learning jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Junior Aws Machine Learning jobs in Washington look for?

The top searched job categories for Junior Aws Machine Learning jobs in Washington are:

What cities in Washington are hiring for Junior Aws Machine Learning jobs?

Cities in Washington with the most Junior Aws Machine Learning job openings:

Junior Aws Machine Learning jobs near you
Infographic showing various Junior Aws Machine Learning job openings in Washington as of June 2026, with employment types broken down into 30% Full Time, 69% Part Time, and 1% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.

Sr. Machine Learning Engineer

Hirekeyz Inc

Fort Belvoir, VA • On-site

$118K - $162K/yr

Contractor

Re-posted 7 days ago

Job description

Role: Sr. Machine Learning Engineer

Location: Ft. Belvoir, VA (On-site with Hybrid Option)

Duration: Long Term Contract

Clearance: DOD Top Secret Clearance (Must)

Job Description:

As a consultant, will be working to assist a DoD U.S. Army Command to create cybersecurity solutions working with cloud-based architecture (AWS Services).  You will work directly the stakeholders to understand requirements and work with Army’s Security teams to ensure the technologies available to the Government can be turned into solutions that they can use. Liaise with government software vendors and other asset creators; lead coordination of point solutions into broader capabilities for Army Defense Cyber Operations (DCO).  You will be helping our military defend our cyber security infrastructure by delivering software capabilities. 

Required Skills:

  • Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field
  • Master’s Degree in Data Science, Machine Learning, or a related field
  • Proven experience in a machine learning or AI engineering role
  • Strong proficiency in Python, C++, or Java
  • Extensive experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras
  • Familiarity with cloud platforms (AWS, Google Cloud, Azure) for deploying ML solutions
  • Experience with data preprocessing, feature engineering, and model selection
  • Knowledge of data structures, algorithms, and software architecture
  • Excellent problem-solving abilities and attention to detail
  • Strong communication skills, with the ability to present complex technical concepts to non-technical stakeholders
  • Commitment to writing clean, efficient, and well-tested code
  • Self-motivated, with the ability to work effectively both independently and in a team environment

Preferred Skills:

  • Certifications in Machine Learning / Artificial Intelligence / Data Science
  • Familiarity with agile development methodologies
  • 3-5 years of experience in a ML/AI development role