ALOIS Solutions
AI/ML Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI/ML Engineer in Stanford, CA, hybrid (2 days on campus), with a contract length of unspecified duration. Pay rate is also unspecified. Requires 3+ years in AI/ML applications, Python, AWS experience, and an AWS Associate certification.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
488
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🗓️ - Date
February 11, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Stanford, CA
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🧠 - Skills detailed
#TypeScript #AI (Artificial Intelligence) #Python #Langchain #SageMaker #MS SQL (Microsoft SQL Server) #GIT #API (Application Programming Interface) #Computer Science #GitHub #DevOps #Automation #Lambda (AWS Lambda) #AWS SageMaker #Data Engineering #S3 (Amazon Simple Storage Service) #Infrastructure as Code (IaC) #Scala #"ETL (Extract #Transform #Load)" #Docker #Monitoring #ML (Machine Learning) #Microservices #SQL (Structured Query Language) #AWS (Amazon Web Services) #Data Pipeline #TensorFlow #IAM (Identity and Access Management) #Cloud #NoSQL #PyTorch #Databases #R
Role description
Title: AI/ML Engineer
Location: Stanford, CA 94305 Hybrid (2 days on campus)
Job Description:
Top 3 requirements:
1. 3+ years deploying AI/ML applications in production
1. Python + AWS experience
1. At least one AWS Associate level certification
• The AI/ML Engineer is a key technical contributor driving CGOE’s AI transformation initiatives.
• This role focuses on building and deploying intelligent, cloud-native applications—from GenAI-powered systems and retrieval-augmented assistants to data-driven automation workflows.
• Working at the intersection of machine learning, cloud engineering, and educational innovation, the engineer translates complex needs into scalable, secure, and maintainable AWS-native AI systems that enhance teaching, learning, and operations across CGOE’s global online programs.
Required Qualifications:
Education & Certifications:
• Bachelor’s degree in Computer Science, AI/ML, Data Engineering, or a related field (Master’s preferred).
• AWS certification preferred (Solutions Architect, Developer, or equivalent); Professional-level certification a plus.
Experience:
• 3+ years of experience developing and deploying AI/ML-driven applications in production.
• 2+ years of hands-on experience with AWS-based architectures (serverless, microservices,
• CI/CD, IAM).
• Proven ability to design, automate, and maintain data pipelines for model inference, evaluation, and monitoring.
• Experience with both GenAI and traditional ML techniques in applied, production settings.
Technical Skills:
• Languages: Python (required); familiarity with Go, Rust, R, or TypeScript preferred.
• AI/ML Frameworks: PyTorch, TensorFlow, LangChain, LlamaIndex, or similar.
• Cloud & Infrastructure: AWS SageMaker, Bedrock, Lambda, ECS/Fargate, API Gateway, EventBridge, Glue, S3, Step Functions, IAM, CloudWatch.
• Infrastructure as Code: AWS CloudFormation.
• DevOps & Tools: Git, Docker, AWS Fargate, ECS, CI/CD (GitHub Actions, CodePipeline).
• Data Systems: SQL/NoSQL, vector databases, and AWS-native data services.
Title: AI/ML Engineer
Location: Stanford, CA 94305 Hybrid (2 days on campus)
Job Description:
Top 3 requirements:
1. 3+ years deploying AI/ML applications in production
1. Python + AWS experience
1. At least one AWS Associate level certification
• The AI/ML Engineer is a key technical contributor driving CGOE’s AI transformation initiatives.
• This role focuses on building and deploying intelligent, cloud-native applications—from GenAI-powered systems and retrieval-augmented assistants to data-driven automation workflows.
• Working at the intersection of machine learning, cloud engineering, and educational innovation, the engineer translates complex needs into scalable, secure, and maintainable AWS-native AI systems that enhance teaching, learning, and operations across CGOE’s global online programs.
Required Qualifications:
Education & Certifications:
• Bachelor’s degree in Computer Science, AI/ML, Data Engineering, or a related field (Master’s preferred).
• AWS certification preferred (Solutions Architect, Developer, or equivalent); Professional-level certification a plus.
Experience:
• 3+ years of experience developing and deploying AI/ML-driven applications in production.
• 2+ years of hands-on experience with AWS-based architectures (serverless, microservices,
• CI/CD, IAM).
• Proven ability to design, automate, and maintain data pipelines for model inference, evaluation, and monitoring.
• Experience with both GenAI and traditional ML techniques in applied, production settings.
Technical Skills:
• Languages: Python (required); familiarity with Go, Rust, R, or TypeScript preferred.
• AI/ML Frameworks: PyTorch, TensorFlow, LangChain, LlamaIndex, or similar.
• Cloud & Infrastructure: AWS SageMaker, Bedrock, Lambda, ECS/Fargate, API Gateway, EventBridge, Glue, S3, Step Functions, IAM, CloudWatch.
• Infrastructure as Code: AWS CloudFormation.
• DevOps & Tools: Git, Docker, AWS Fargate, ECS, CI/CD (GitHub Actions, CodePipeline).
• Data Systems: SQL/NoSQL, vector databases, and AWS-native data services.
