Job Specifications
Job Title: AI/ML Engineer
Duration: 12 Months
Location: Stanford, CA
Pay Rate: $62.14/hr
Job Description:
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.
Apply containerization best practices using Docker and manage workloads through AWS Fargate and ECS for scalable, serverless orchestration and reproducibility.
Ensure compliance with Cient and regulatory standards (FERPA, GDPR) for secure data handling and governance.
Collaboration, Culture & Continuous Improvement
Collaborate closely with cross-functional teams to deliver integrated and impactful AI solutions.
Use Git-based version control and code review best practices as part of a collaborative, agile workflow.
Operate within an agile, iterative development culture, participating in sprints, retrospectives, and planning sessions.
Continuously learn and adapt to emerging AI frameworks, AWS tools, and cloud technologies. Contribute to documentation, internal knowledge sharing, and mentoring as the team scales.
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.
Equal Employment Opportunity Statement
Intelliswift celebrates a diverse and inclusive workforce. We offer equal employment opportunities to all applicants and employees. All qualified applicants will be considered regardless of race, color, sex, gender identity, gender expressions, religion, age, national origin or ancestry, citizenship, physical or mental disability, medical condition, family care status, marital status, domestic partner status, sexual orientation, genetic information, military or veteran status, or any other protected basis under the law.
Americans with Disabilities Act (ADA)
If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please contact Intelliswift Human Resources Department
Other Employment Statements
Intelliswift participates in the E-Verify program.
Learn More
For information on Intelliswift Software, Inc., visit our website at www.intelliswift.com.
About the Company
Intelliswift, an LTTS company, is a global leader in Digital Product Engineering, Data & AI, and Digital Enterprise Solutions. We empower businesses to leverage cutting-edge technologies and pioneering strategies throughout their digital transformation journey. Our expertise in data-rich modern platforms and people-centric solutions ensures that companies can navigate and thrive in the digital era. We address critical pain points across a diverse range of industries, including Platform & Technology, Fintech, MedTech, Energy ...
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