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Amazon Computer Science Internship Jobs in Riverside, CA

Syntiant

Model Converter Engineer Intern

Irvine, CA · On-site

$18 - $23.25/hr

Bachelor's or Master's student in Computer Science or Computer Engineering is required. * Relevant ... Amazon Alexa Fund, and Atlantic Bridge Capital. More information on the company can be found by ...

Syntiant

Model Converter Engineer Intern

Irvine, CA

$18 - $23.25/hr

Bachelor's or Master's student in Computer Science or Computer Engineering is required. * Relevant ... Amazon Alexa Fund, and Atlantic Bridge Capital. More information on the company can be found by ...

Syntiant

Model Converter Engineer Intern

Irvine, CA · On-site

$18 - $23.25/hr

Bachelor's or Master's student in Computer Science or Computer Engineering is required. * Relevant ... Amazon Alexa Fund, and Atlantic Bridge Capital. More information on the company can be found by ...

Esri

System Engineer- Enterprise Data Engineer

Redlands, CA · On-site

$107K - $133K/yr

One or more industry-standard IT certifications (such as Esri, Microsoft, Amazon, PostgreSQL, Oracle) * Master's degree in computer science, mathematics, GIS or related STEM field #LI-SS2 #LI-Onsite

Esri

Sr. Application Developer - Entitlement

Redlands, CA · On-site

$96K - $132K/yr

Bachelor's degree in information systems, computer science, engineering, or related field Recommended Qualifications * Knowledge of cloud computing platforms and services such as Amazon S3, SQS, EC2 ...

VSolvit

JUNIOR SOFTWARE DEVELOPER (C++)

Norco, CA · On-site

$75K - $110K/yr

Candidates with internship experience, academic projects, personal software projects, or ... Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related ...

Zorts Sports

Software Engineer

Claremont, CA · Remote

What Were Looking For Core Qualifications * 1+ year of professional (non-internship) software development experience * Strong foundation in computer science fundamentals, algorithms, and data ...

SwiftX Inc.

Operation Expert

Ontario, CA · On-site

Requirements Bachelor's or Master's degree in Data Science, Computer Science, Logistics, Business ... projects, internships, or entry-level roles is acceptable. Must be bilingual in Mandarin and ...

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Amazon Computer Science Internship information

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How much do amazon computer science internship jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for amazon computer science internship in Riverside, CA is $26.52, according to ZipRecruiter salary data. Most workers in this role earn between $21.59 and $30.10 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Amazon Computer Science Intern, and why are they important?

To thrive as an Amazon Computer Science Intern, you need a solid understanding of computer science fundamentals, programming languages like Java or Python, and currently be enrolled in a relevant degree program. Familiarity with version control systems (e.g., Git), cloud platforms such as AWS, and debugging or development tools is typically expected. Strong problem-solving, teamwork, and effective communication skills help interns collaborate and learn quickly in a fast-paced environment. These abilities enable interns to contribute meaningfully to projects, adapt to Amazon’s dynamic culture, and maximize their learning experience.

What is an Amazon Computer Science Internship?

An Amazon Computer Science Internship is a paid, hands-on opportunity for students studying computer science or related fields to gain real-world experience at Amazon. Interns work alongside experienced engineers on impactful projects, often involving software development, systems engineering, or data analysis. The program typically runs for 12-16 weeks during the summer and offers mentorship, networking, and potential pathways to full-time roles. Interns can expect to enhance their technical skills, contribute to innovative solutions, and learn about Amazon’s culture and technologies.

What types of projects do Amazon Computer Science Interns typically work on, and how are they assigned?

Amazon Computer Science Interns are usually assigned to real-world projects that have a tangible impact on the company's products and services. These projects can range from developing scalable web services, improving machine learning models, to optimizing backend systems for performance. Interns are matched with teams based on their skill set, interests, and the needs of the business, ensuring a meaningful learning experience. Collaboration is key: interns work closely with experienced engineers, participate in code reviews, and often present their solutions to stakeholders. This hands-on environment helps interns build both technical and teamwork skills.
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Amazon Computer Science Internship jobs near you

Senior AI Engineer (GenAI and Data Platform - AWS)

Saransh Inc

Irvine, CA • On-site

$131K - $173K/yr

Contractor

Posted yesterday

Job description

Role: Senior AI Engineer (GenAI + Data Platform – AWS)
Location: 4 days a week onsite is must (3 days in Irvine, CA & 1 Day in Downtown, LA, CA)
Job Type: Contract

Role Summary:
  • We are seeking a Senior AI Engineer to design, build, and scale a production-grade Generative AI and Data Platform on AWS.
  • The role focuses on enabling LLM-powered capabilities through vector search, graph-based knowledge systems, and governed data pipelines.
Note:
Must Have Skills:
  • Generative AI / LLM (RAG, embeddings, prompt engineering)
  • AWS Cloud (OpenSearch, Neptune, DynamoDB, ElastiCache/Redis)
  • Vector Search & Retrieval Systems (OpenSearch / vector DB)
  • Graph Databases (Amazon Neptune, knowledge graphs)
  • LLM Frameworks (LangChain / LlamaIndex)
  • Agentic AI Frameworks (LangGraph / AutoGen / CrewAI)
  • Databricks & Apache Spark (data pipelines, embedding pipelines)
  • Backend/API Development (Python, scalable APIs, microservices)

Must Have Certifications:
AWS Certification (Preferred):
  • AWS Certified Solutions Architect OR
  • AWS Certified Machine Learning Specialty OR
  • AWS Data Engineer Certification

The ideal candidate will own end-to-end delivery across the AI lifecycle, including:
  • Data ingestion and knowledge curation
  • Embeddings and retrieval systems
  • Backend services and APIs
  • CI/CD pipelines and deployment
Key Responsibilities:
1. GenAI Enablement & Integration
 
Build and operationalize LLM-powered applications using:
  • Retrieval-Augmented Generation (RAG)
  • Embeddings pipelines
  • Prompt orchestration and evaluation frameworks
  • Design and implement vector search systems using Amazon OpenSearch
  • Develop graph-based knowledge systems using Amazon Neptune for relationships, lineage, and explainability
Integrate supporting infrastructure:
  • Amazon ElastiCache (Redis) for session state and caching
  • DynamoDB for scalable, low-latency data access
 
Implement agentic workflows using frameworks such as:
LangGraph, AutoGen, CrewAI (or equivalent)
Integrate with LLM frameworks like:
LangChain, LlamaIndex (tool calling, retrieval orchestration, context management)
Define standards for:
Tool integration
Context-sharing patterns (MCP-style designs)
Evaluate LLM models and retrieval strategies across:
Latency
Cost
Accuracy
Context limitations
 
2. Data Pipelines & Knowledge Engineering
Design and build scalable data pipelines using Databricks and Apache Spark
Implement:
  • Data ingestion and transformation pipelines
  • Document processing (chunking, metadata tagging)
  • Embedding generation and indexing
Ensure high data quality standards:
Validation, completeness, consistency, monitoring
 
Implement data governance frameworks:
  • Data classification and access controls
  • Retention policies
  • Auditability and lineage tracking
3. Backend Services & APIs
Develop backend services exposing AI capabilities through secure and scalable APIs
Define best practices for:
API contracts and versioning
Reliability (retry logic, circuit breakers, idempotency)
Enable reusability of platform capabilities across teams and applications.
 
4. Deployment, MLOps & Operational Excellence
Build and manage CI/CD pipelines for AI and data workloads
Deploy production systems using:
Docker (containerization)
Kubernetes (orchestration)
Implement deployment strategies:
Blue/green deployments
Canary releases
Rollback strategies
Feature flags
Ensure system reliability through:
Monitoring (latency, failures, cost, data freshness)
Alerting and observability
Secrets management and least-privilege access
Optimize platform performance and cost
 
5. LLM Observability, Evaluation & Quality
Define and track GenAI quality metrics:
Grounding / faithfulness
Retrieval relevance
Response consistency
Latency and cost per request
Implement:
Prompt/version tracking
Offline evaluation pipelines
Continuous improvement workflows
 
6. LLM Security, Safety & Compliance
Implement secure AI systems with:
Access control and authentication
Data protection policies
Responsible AI guardrails
Ensure compliance with best practices in:
AI safety
Data privacy
Monitoring and auditability
Required Skills:
  • Strong experience in Generative AI / LLM systems (RAG, embeddings, prompt engineering)
  • Hands-on experience with AWS ecosystem
Expertise in:
  • OpenSearch (vector search)
  • Neptune (graph databases)
  • DynamoDB and Redis (ElastiCache)
Experience with:
  • LangChain / LlamaIndex
  • Agentic AI frameworks (LangGraph, AutoGen, CrewAI)
  • Strong programming skills (Python preferred)
  • Experience with Databricks and Apache Spark
Solid understanding of:
  • Data pipelines
  • Distributed systems
  • API design
Preferred Skills:
Experience with:
  • Model evaluation frameworks and LLM observability tools
  • AI governance and compliance frameworks
  • Kubernetes and advanced MLOps practices
Familiarity with:
  • Model Context Protocol (MCP) patterns
  • Agent-based architectures
Qualifications:
  • Bachelor’s or Master’s degree in: Computer Science / Data Science / AI / related field
  • Proven experience building production-grade AI platforms and systems
  • Strong background in end-to-end AI/ML lifecycle delivery.