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Aws Machine Learning Engineer Jobs (NOW HIRING)

Givzey

Machine Learning Engineer

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to ... AWS Certified Machine Learning - Specialty or AWS Certified Big Data - Specialty * Experience with ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed ...

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed ...

Full Scope

Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly ... Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No ... Putting your model into production using AWS or GCP. Required Qualifications * BS. in Computer ...

ExtendMyTeam

Machine Learning Engineer

Cary, NC

This is a hands-on engineering role focused on production systems, model deployment, APIs ... Exposure to cloud platforms such as AWS, GCP, or Azure * Understanding of taking machine learning ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or ... Experience with Linux, Docker and AWS, and basic development operations. * Advanced degree in ...

Pattern AI

Machine Learning Engineer

San Mateo, CA

Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or ... Experience with Linux, Docker and AWS, and basic development operations. * Advanced degree in ...

Atrium

Contract Machine Learning Engineer

Manhattan, NY · On-site

$75 - $110/hr

This Contract Machine Learning Engineer will work closely with Data Science, DevOps, Cloud ... Manage and optimize cloud-based ML environments across AWS, Azure, or GCP. * Implement model ...

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Aws Machine Learning Engineer information

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$31.5K

$128.8K

$193.5K

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

As of May 30, 2026, the average yearly pay for aws 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 are the key skills and qualifications needed to thrive as an AWS Machine Learning Engineer, and why are they important?

To thrive as an AWS Machine Learning Engineer, you need strong proficiency in machine learning algorithms, programming languages like Python, and a solid understanding of cloud architecture, typically supported by a degree in computer science or a related field. Familiarity with AWS services such as SageMaker, Lambda, and S3, as well as relevant certifications like AWS Certified Machine Learning – Specialty, is highly valuable. Strong problem-solving, collaboration, and communication skills set top performers apart in this role. These skills ensure successful design, deployment, and optimization of scalable machine learning solutions on AWS that meet business needs.

How does an AWS Machine Learning Engineer typically collaborate with data scientists and DevOps teams?

As an AWS Machine Learning Engineer, you’ll work closely with data scientists to operationalize models, ensuring they are scalable and production-ready on AWS platforms. You’ll also frequently collaborate with DevOps teams to automate deployment pipelines, monitor model performance, and manage infrastructure using AWS services like SageMaker, Lambda, and CloudFormation. This cross-functional teamwork is essential for maintaining reliable, efficient ML workflows and for quickly resolving issues that arise in live environments.

What are AWS Machine Learning Engineers?

AWS Machine Learning Engineers are specialized professionals who design, build, deploy, and manage machine learning models using Amazon Web Services (AWS) cloud infrastructure. They leverage AWS tools and services, such as SageMaker, to create scalable and efficient machine learning solutions for businesses. Their responsibilities include data preparation, model training, optimization, deployment, and monitoring in a cloud environment. AWS Machine Learning Engineers often collaborate with data scientists, software engineers, and DevOps teams to integrate machine learning models into production systems.

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

AspectAws Machine Learning EngineerData Scientist
CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, deployment pipelinesData analysis, modeling, research environments
Industry UsageTech, finance, healthcare using AWS for ML solutionsResearch, analytics, business intelligence
Search/Comparison IntentFocus on cloud-based ML deployment and engineeringFocus on data analysis and modeling

While both roles involve working with data and machine learning, Aws Machine Learning Engineers specialize in deploying ML models on AWS cloud platforms, focusing on infrastructure and scalable solutions. Data Scientists primarily analyze data, build models, and generate insights, often using a variety of tools and programming languages. The roles overlap in skills but differ in their primary focus and work environment.

More about Aws Machine Learning Engineer jobs
What states have the most Aws Machine Learning Engineer jobs? States with the most job openings for Aws Machine Learning Engineer jobs include:
What job categories do people searching Aws Machine Learning Engineer jobs look for? The top searched job categories for Aws Machine Learning Engineer jobs are:
Aws Machine Learning Engineer jobs near you
Infographic showing various Aws Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 69% Full Time, 24% Part Time, and 7% Contract. Highlights an 72% Physical, 5% Hybrid, and 23% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

Givzey

Remote

Full-time

Posted 28 days ago

Job description

Machine Learning Engineer
We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity to shape and create our machine learning capabilities from the ground up. You'll be at the forefront of innovation, designing and implementing ML systems that drive our business forward.
Responsibilities:
  • Design, develop, and implement machine learning models and algorithms
  • Analyze large datasets and extract meaningful insights
  • Collaborate with cross-functional teams to integrate ML solutions into existing systems
  • Optimize ML models for performance and scalability
  • Stay current with the latest advancements in machine learning and AI
  • Create and implement big data processing pipelines and architectures
  • Design and build scalable data infrastructure to support ML applications
Requirements:
  • US Citizen
  • Bachelor's or Master's degree in Computer Science, Data Science, or related field
  • 3+ years of experience in machine learning or AI development
  • Strong proficiency in Python and its ML/data science libraries (e.g., TensorFlow, PyTorch, scikit-learn, pandas)
  • Solid understanding of machine learning algorithms and statistical modeling
  • Experience with big data technologies (e.g., Hadoop, Spark, Kafka)
  • Proven ability to create and implement big data solutions from scratch
  • Comfortable setting up and managing distributed computing environments
  • Experience in designing and implementing data pipelines for large-scale data processing
  • Proficient in working with various database systems, both SQL and NoSQL, depending on the use case
  • Strong skills in data modeling and database design for machine learning applications
  • Excellent problem-solving and analytical skills
  • Strong communication skills and ability to work in a team environment
Preferred Qualifications:
  • Experience in creating and managing real-time data streaming architectures
  • AWS Certified Machine Learning - Specialty or AWS Certified Big Data - Specialty
  • Experience with AWS machine learning services
  • Proficiency in using AWS big data services
  • Knowledge of serverless architectures on AWS (e.g., Lambda)
  • Experience in creating and managing real-time data streaming architectures on AWS (e.g., Kinesis)
  • Understanding of AWS security best practices for machine learning and data processing workflows

What you'll do day-to-day:
  • Be a member of a world-class team focused on inventing solutions that have the ability to impact the world
  • Tackle a wide variety of technical problems throughout the stack and contribute daily to all parts of our product code base
  • Help build a beautiful, intuitive product that revolutionizes the nonprofit industry
  • Work closely with our customers, founders, team members and Board to understand customer pain points, develop solutions, and prototype, iterate, and deploy code on regular cycles
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About Givzey

Sourced by ZipRecruiter

Industry

Administrative assistance services

Company size

1 - 10 Employees

Headquarters location

Boston, MA, US

Year founded

2021

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