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Aws Ml Jobs (NOW HIRING)

Saransh Inc

AI/ML Architect

Irvine, CA · On-site

$68.50 - $88/hr

AWS Cloud (Cloud-Native Development) * CI/CD & DevOps Practices * Observability (Logging, Monitoring, Tracing) Responsibilities: * Design and develop scalable AI/ML pipelines and intelligent ...

Cloudelligent

AWS Solutions Architect- AI/ML

Dallas, TX · On-site

$64 - $84/hr

AWS Solutions Architect- AI/ML Employment Time: Full-Time This Is a fully remote position with travel required. About Cloudelligent Cloudelligent is an AWS Premier Consulting Partner helping ...

Cloudelligent

AWS Solutions Architect- AI/ML

Dallas, TX · On-site

$64 - $84/hr

AWS Solutions Architect- AI/ML Employment Time: Full-Time This Is a fully remote position with travel required. About Cloudelligent Cloudelligent is an AWS Premier Consulting Partner helping ...

Cloudelligent

AWS Solutions Architect- AI/ML

Austin, TX · On-site

$64.25 - $84.25/hr

AWS Solutions Architect- AI/ML Employment Time: Full-Time This Is a fully remote position with travel required. About Cloudelligent Cloudelligent is an AWS Premier Consulting Partner helping ...

Cloudelligent

AWS Solutions Architect- AI/ML

Austin, TX · On-site

$64.25 - $84.25/hr

AWS Solutions Architect- AI/ML Employment Time: Full-Time This Is a fully remote position with travel required. About Cloudelligent Cloudelligent is an AWS Premier Consulting Partner helping ...

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Aws Ml information

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How much do aws ml jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for aws ml 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 skills and qualifications are needed to thrive as an AWS ML engineer?

To thrive as an AWS Machine Learning (ML) Engineer, you need a solid background in machine learning algorithms, programming (Python or R), and a 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 valued. Strong problem-solving, collaboration, and communication skills help you translate business needs into technical solutions and work effectively in a team. These competencies are crucial for designing scalable ML models and deploying them efficiently on AWS to drive data-driven business outcomes.

What is an AWS ML engineer?

AWS ML engineers are professionals who design, build, and deploy machine learning models using Amazon Web Services (AWS) cloud platform. They utilize AWS services like SageMaker, Lambda, and EC2 to manage data, train algorithms, and scale machine learning solutions. Their expertise allows businesses to leverage AI and ML technologies efficiently and securely in the cloud.

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

AWS ML engineers often encounter challenges such as managing model versioning, ensuring scalability, and integrating with existing data pipelines during deployment. Navigating AWS services like SageMaker for automation, monitoring, and cost optimization requires both technical skill and close collaboration with data scientists and DevOps teams. Additionally, staying updated with AWS's rapidly evolving ML toolset is essential to leverage new features and maintain efficient, secure production environments.

What is the difference between Aws Ml vs Data Scientist?

AspectAws MlData Scientist
Required CredentialsAWS certifications, programming skills (Python, SQL)Statistics, machine learning, programming (Python, R)
Work EnvironmentCloud platforms, AWS servicesData analysis, research, modeling
Industry UsageCloud-based AI/ML solutions, deploymentData analysis, predictive modeling, research

While Aws Ml specialists focus on deploying machine learning models using AWS cloud services, Data Scientists analyze data and develop models often using various tools and programming languages. Both roles require strong technical skills, but Aws Ml professionals are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and model development.

More about Aws Ml jobs
What states have the most Aws Ml jobs? States with the most job openings for Aws Ml jobs include:
What job categories do people searching Aws Ml jobs look for? The top searched job categories for Aws Ml jobs are:
Aws Ml jobs near you
Infographic showing various Aws Ml job openings in the United States as of August 2026, with employment types broken down into 89% Full Time, 1% Part Time, and 10% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $145,725 per year, or $70.1 per hour.

AI/ML Architect

Saransh Inc

Irvine, CA • On-site

$68.50 - $88/hr

Contractor

Re-posted 22 days ago

Job description

Role: AI Scientist / AI Architect
Location: 4 days a week onsite is must (3 days in Irvine, CA & 1 Day in Downtown, LA, CA)
Job Type: Contract
Description:
  • A highly skilled hands-on AI Scientist / Architect with at least 8+ years of experience in AI/ML, Data Science, or Software Engineering.
  • You bring strong expertise in designing and building scalable, production-ready AI solutions, with deep hands-on experience in LLM-enabled applications, agent-based systems, and cloud-native architectures.
  • You are comfortable working closely with business stakeholders and leading AI-driven innovation initiatives in an enterprise environment.
Note:
Mandatory Areas:
  • AI/ML Solution Architecture
  • LLM & Generative AI Development
  • Agent-Based Systems
  • Retrieval-Augmented Systems (RAG)
  • Enterprise AI Integration
  • AI/ML, Data Science, AI Architecture, Python, LLM, CI/CD
Must Have Skills:
• Python & Backend Development
• LLM / Generative AI Application Development
• Agent-Based AI Systems
• RAG / Vector DB / Embeddings
• API Development & System Integration
• AWS Cloud (Cloud-Native Development)
• CI/CD & DevOps Practices
• Observability (Logging, Monitoring, Tracing)
Responsibilities:
  • Design and develop scalable AI/ML pipelines and intelligent applications aligned with enterprise standards
  • Build agent-based AI workflows, automation systems, and retrieval-based architectures (RAG, vector search, embeddings)
  • Architect and implement LLM orchestration layers supporting content ideation, drafting, and editing workflows
  • Lead integration of AI solutions with backend systems and enterprise platforms (APIs, internal tools, data platforms)
  • Partner with product, marketing, and business stakeholders to translate requirements into AI-driven solutions
  • Provide architectural leadership, guide offshore teams, and ensure delivery aligned with scalability, security, and governance standards.
Requirements:
  • At least 8+ years of experience in AI/ML, Data Science, or Software Engineering
  • Strong Python backend development experience
  • Hands-on experience with LLM-enabled applications and Generative AI
  • Experience building agent-based / agent-oriented AI systems
  • Strong expertise in retrieval-based systems (RAG, vector databases, embeddings, indexing)
  • Experience with API development and backend system integration.
  • AWS cloud-native development experience
  • Experience with CI/CD pipelines and environment management
  • Strong understanding of observability (logging, monitoring, tracing)
  • Experience deploying ML models in production environments
  • Exposure to enterprise AI workflows, automation, and governance models.
Domain Experience (If any):
• AI-enabled enterprise workflows
• Marketing / Content generation platforms (nice to have)
• Financial / Investment domain (preferred based on content use cases)
Certifications:
• Not mandatory (AWS / ML / AI certifications are good to have)