AI/ML Engineer

AI/ML Engineer 1464457

• Hourly pay: $60/hr
• Worksite: Leading university (Stanford, CA 94305 - Hybrid, Must be onsite 2–3 days on campus)
• W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL
• 40 hours/week, 12 Month Assignment, Possible extension or conversion

A leading university seeks an AI/ML Engineer. The successful candidate will focus on building and deploying intelligent, cloud-native applications—from GenAI-powered systems and retrieval-augmented assistants to data-driven automation workflows. The company offers a family-oriented culture and environment!

AI/ML Engineer Responsibilities:

• AI Application & Systems Development:
  • Own the design and end-to-end implementation of AI systems combining GenAI, narrow AI, and traditional ML models (e.g., regression, classification).
  • Implement retrieval-augmented generation (RAG), multi-agent, and protocol-based AI systems (e.g., MCP).
  • Integrate AI capabilities into production-grade applications using serverless and containerized architectures (AWS Lambda, Fargate, ECS).
  • Fine-tune and optimize existing models for specific educational and administrative use cases, focusing on performance, latency, and reliability.
  • Build and maintain data pipelines for model training, evaluation, and monitoring using AWS services such as Glue, S3, Step Functions, and Kinesis.
• Cloud & Infrastructure Engineering:
  • Architect and manage scalable AI workloads on AWS, leveraging services such as SageMaker, Bedrock, API Gateway, EventBridge, and IAM-based security.
  • Build microservices and APIs to integrate AI models into applications and backend systems.
  • Develop automated CI/CD pipelines ensuring continuous delivery, observability, and monitoring of deployed workloads.
    
    

AI/ML Engineer Qualifications:

• 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).
• Bachelor’s degree in Computer Science, AI/ML, Data Engineering, or a related field (Master’s preferred).
• AWS certification (Solutions Architect, Developer, or equivalent); Professional-level certification.
• 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.
• 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.
• A strong understanding of data engineering fundamentals and production-quality AI system design is preferred.
• A passion for applying AI to enhance educational outcomes and operational efficiency is preferred.
• Excellent problem-solving, debugging, and communication skills are preferred.
• Demonstrated ability to learn rapidly, adapt to new technologies, and continuously improve is preferred.
• Commitment to ethical AI, data privacy, and transparency is preferred.
• A collaborative mindset with proven success in agile, team-based environments is preferred.

Shift:

• Monday to Friday 9 am - 6 pm.