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Aws Machine Learning Jobs (NOW HIRING)

Itransition Group

NY · On-site

Strong Python skills and experience with ML ecosystems (AWS Sagemaker, MLFlow) * Hands‑on experience working with tabular/time series data with usage of ML * Solid understanding of machine learning ...

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How much do aws machine learning jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for aws machine learning in the United States is $70.06, according to ZipRecruiter salary data. Most workers in this role earn between $62.26 and $81.73 per hour, depending on experience, location, and employer.

What is an AWS Machine Learning?

An AWS Machine Learning job involves designing, building, and deploying machine learning models using Amazon Web Services (AWS) cloud infrastructure. Professionals in this role work with services like Amazon SageMaker, AWS Lambda, and AWS Glue to develop AI-driven applications. They optimize models for scalability, integrate them into cloud-based systems, and ensure efficient data processing. Strong knowledge of machine learning algorithms, AWS architecture, and MLOps best practices is essential for success in this role.

What does an AWS Machine Learning do?

In an AWS Machine Learning position, you'll typically design, develop, and deploy machine learning models using AWS services like SageMaker, Glue, and Lambda. Daily tasks often include data preprocessing, building and training models, and optimizing performance for production environments. You'll collaborate closely with data engineers, software developers, and business analysts to translate business needs into technical solutions. The role may also involve monitoring deployed models, managing cloud resources, and staying updated on new AWS features to ensure efficient and scalable machine learning workflows.

What are the key skills and qualifications needed for an AWS Machine Learning?

To thrive as an AWS Machine Learning professional, you need a strong understanding of machine learning principles, proficiency in programming languages like Python, and experience with AWS cloud services such as SageMaker. AWS Certified Machine Learning certification and familiarity with data pipelines, EC2, and Lambda are commonly required. Strong problem-solving, communication, and teamwork skills help you translate business requirements into technical solutions and collaborate effectively with diverse stakeholders. These skills are essential to efficiently deploy and manage scalable machine learning models that deliver business value in cloud-based environments.

Does AWS use machine learning?

AWS offers a wide range of machine learning services and tools, such as Amazon SageMaker, which enable developers and data scientists to build, train, and deploy machine learning models. As a cloud provider, AWS integrates machine learning into its infrastructure to support various applications, making it a key platform for machine learning professionals. Knowledge of AWS services and machine learning concepts is valuable for roles like AWS Machine Learning specialists.

Is AWS Machine Learning a high paying job?

AWS Machine Learning roles are generally well-paid due to the specialized skills required, such as expertise in cloud computing, data science, and machine learning frameworks. Salaries vary based on experience, location, and certifications, but they tend to be higher than average for tech roles with similar responsibilities.
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AWS Machine Learning jobs near you
Infographic showing various Aws Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $145,725 per year, or $70.1 per hour.

Senior Machine Learning Solutions Architect

Remote

Empower
Advertising and Public Relations Services • 51 - 200 employees
Learn more about Empowerexternal

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago

Job description

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them.

Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself.

***Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time, including CPT/OPT.***

As a Senior Machine Learning Solution Architect, you will shape how machine learning and advanced analytics are designed, delivered, and scaled across the organization. You will own the architectural patterns that move data from fragmented sources into production grade machine learning, analytics, and AI use cases that directly power business outcomes.

This role sits at the intersection of data, machine learning, and application architecture, defining how data is structured, moved, and activated to enable personalization, marketing, reporting, and real time decisioning. This includes enabling feature engineering, model training pipelines, experimentation workflows, and model evaluation frameworks at scale. You will partner with data scientists, engineers, and product teams to turn modeling efforts into scalable production systems, focusing on solving real constraints and enabling consistent, reusable capabilities across the enterprise.

What You Will Do

  • Architect end to end machine learning solutions from data ingestion through production consumption across multiple business use cases

  • Design and standardize how data flows across systems to support machine learning, analytics, personalization, and real time decisioning

  • Define the architectural patterns that support feature engineering, model training workflows, experimentation, and model evaluation at scale

  • DefineMLOpspatterns that enable consistent deployment, monitoring, and lifecycle management of models at scale

  • Build reusable capabilities such as feature pipelines, model serving frameworks, and data access patterns

  • Define how machine learning and analytical outputs are exposed through APIs, batch processes, and real time services

  • Partner with data scientists and engineers to remove friction between experimentation and production while driving key architectural decisions

What You Will Bring

  • Bachelor's degree in Data Science, Statistics, Computer Science, or a closely related quantitative field

  • 8 plus years of experience in data, platform, or software engineering roles with exposure to machine learning or advanced analytics

  • Experience designing and delivering production grade machine learning or advanced analytics solutions

  • Strong background in data architecture and data movement across distributed systems

  • Deep understanding of machine learning workflows including feature engineering, model training, experimentation, evaluation, and production deployment

  • Experience with modern data and machine learning platforms such as AWS, Snowflake, Databricks, or similar

What You Will Set You Apart

  • Experience designing systems that directly enable personalization, marketing activation, or customer level decisioning

  • Experience building or scalingMLOpscapabilities beyond experimentation into production use

  • Experience working with real time or event driven data and machine learning use cases

  • Experience working closely with data scientists to productionize models and scale experimentation into repeatable systems

  • Proven ability to connect machine learning with broader analytics and business workflows

  • Relevant certifications such as AWS Certified Solutions Architect, AWS Machine Learning Specialty, SnowflakeSnowProAdvanced Data Engineer or Data Scientist, Databricks Machine Learning Professional, or Google Professional Machine Learning Engineer

This job operates in a professional office environment.

This job description is not intended to be an exhaustive list of all duties, responsibilities and qualifications of the job. The employer has the right to revise this job description at any time. You will be evaluated in part based on your performance of the responsibilities and/or tasks listed in this job description. You may be required to perform other duties that are not included on this job description. The job description is not a contract for employment, and either you or the employer may terminate employment at any time, for any reason, as per terms and conditions of your employment contract.

What we offer you

We offer an array of diverse and inclusive benefits regardless of where you are in your career. We believe that providing our employees with the means to lead healthy balanced lives results in the best possible work performance.

  • Medical, dental, vision and life insurance
  • Retirement savings - 401(k) plan with generous company matching contributions (up to 6%), financial advisory services, potential company discretionary contribution, and a broad investment lineup
  • Tuition reimbursement up to $5,250/year
  • Business-casual environment that includes the option to wear jeans
  • Generous paid time off upon hire - including a paid time off program plus ten paid company holidays and three floating holidays each calendar year
  • Paid volunteer time - 16 hours per calendar year
  • Leave of absence programs - including paid parental leave, paid short- and long-term disability, and Family and Medical Leave (FMLA)
  • Business Resource Groups (BRGs) - BRGs facilitate inclusion and collaboration across our business internally and throughout the communities where we live, work and play. BRGs are open to all.

Base Salary Range

$138,000.00 - $200,100.00

The salary range above shows the typical minimum to maximum base salary range for this position in the location listed. Non-sales positions have the opportunity to participate in a bonus program. Sales positions are eligible for sales incentives, and in some instances a bonus plan, whereby total compensation may far exceed base salary depending on individual performance. Actual compensation offered may vary from posted hiring range based upon geographic location, work experience, education, licensure requirements and/or skill level and will be finalized at the time of offer.

Equal opportunity employer Drug-free workplace

We are an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age (40 and over), race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.

***For remote and hybrid positions you will be required to provide reliable high-speed internet with a wired connection as well as a place in your home to work with limited disruption. You must have reliable connectivity from an internet service provider that is fiber, cable or DSL internet. Other necessary computer equipment, will be provided. You may be required to work in the office if you do not have an adequate home work environment and the required internet connection.***

Job Posting End Date at 12:01 am on:

09-14-2026

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