Collabera LLC
Detailed Job Description:
Job Title:
AI/Machine Learning Engineer
Client:
Higher Education
Location:
Stanford, CA 94305 – Hybrid (2-3 day onsite)
Duration: 12 Months (Extension/Conversion will be based on the performance)
Pay Range:
($55 – $58) hourly
Top 3 requirements to hire?
3 years deploying AI/Machine Learning applications in production
Python AWS experience
At least one AWS Associate-level certification
Success Metrics:
Timely delivery of scalable, maintainable AI solutions.
High system uptime, performance, and cost-efficiency of deployed workloads.
Consistent adoption of best practices in CI/CD, monitoring, and version control.
Positive stakeholder feedback and contribution to team documentation, learning, and innovation initiatives.ncy
Position Overview
We are seeking an
AI/Machine Learning Engineer
to support enterprise AI transformation initiatives by designing, building, and deploying
cloud-native, production-ready AI solutions .
This role focuses on developing intelligent applications ranging from
GenAI and retrieval-augmented systems to data-driven automation workflows
using AWS-native services.
The ideal candidate combines strong machine learning expertise with cloud engineering skills to deliver scalable, secure, and high-impact AI systems.
Key Responsibilities Design and implement end-to-end
AI/Machine Learning
solutions using GenAI, traditional Machine Learning, and data-driven models.
Build and deploy
RAG , multi-agent, and protocol-based AI systems in production environments.
Integrate AI capabilities into applications using
serverless and containerized AWS architectures .
Fine-tune, optimize, and monitor models for performance, reliability, and scalability.
Develop and maintain data pipelines for model training, inference, and monitoring.
Architect and manage AI workloads on AWS, ensuring security, compliance, and cost efficiency.
Build APIs, microservices, and CI/CD pipelines to support continuous delivery and observability.
Collaborate with cross-functional teams in an agile environment and contribute to documentation and knowledge sharing.
Required Qualifications Bachelor s degree in Computer Science, AI/Machine Learning, Data Engineering, or a related field (Master s preferred).
3 years of experience building and deploying AI/Machine Learning applications in production.
2 years of hands-on experience with
AWS-based architectures
(serverless, microservices, CI/CD).
Strong experience with both
GenAI and traditional Machine Learning techniques
in real-world use cases.
Proficiency in
Python
and experience with modern AI/Machine Learning frameworks.
Technical Skills AI/Machine Learning:
PyTorch, TensorFlow, LangChain, LlamaIndex, or similar frameworks
Cloud & Infrastructure:
AWS SageMaker, Bedrock, Lambda, ECS/Fargate, API Gateway, Glue, S3
DevOps:
Docker, Git, CI/CD pipelines, Infrastructure as Code (CloudFormation)
Data:
SQL/NoSQL databases, vector databases, AWS data services
Preferred Attributes Strong foundation in data engineering and production-grade AI system design.
Excellent problem-solving, communication, and debugging skills.
Passion for applying AI to improve outcomes and operational efficiency.
Commitment to ethical AI, data privacy, and secure system design.
Ability to thrive in a fast-paced, agile, and continuously evolving environment.
Benefits:
The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan, life insurance, long-term disability insurance, short-term disability insurance, paid parking/public transportation, (paid time, paid sick and safe time, hours of paid vacation time, weeks of paid parental leave, paid holidays annually – AS Applicable).
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Job Title:
AI/Machine Learning Engineer
Client:
Higher Education
Location:
Stanford, CA 94305 – Hybrid (2-3 day onsite)
Duration: 12 Months (Extension/Conversion will be based on the performance)
Pay Range:
($55 – $58) hourly
Top 3 requirements to hire?
3 years deploying AI/Machine Learning applications in production
Python AWS experience
At least one AWS Associate-level certification
Success Metrics:
Timely delivery of scalable, maintainable AI solutions.
High system uptime, performance, and cost-efficiency of deployed workloads.
Consistent adoption of best practices in CI/CD, monitoring, and version control.
Positive stakeholder feedback and contribution to team documentation, learning, and innovation initiatives.ncy
Position Overview
We are seeking an
AI/Machine Learning Engineer
to support enterprise AI transformation initiatives by designing, building, and deploying
cloud-native, production-ready AI solutions .
This role focuses on developing intelligent applications ranging from
GenAI and retrieval-augmented systems to data-driven automation workflows
using AWS-native services.
The ideal candidate combines strong machine learning expertise with cloud engineering skills to deliver scalable, secure, and high-impact AI systems.
Key Responsibilities Design and implement end-to-end
AI/Machine Learning
solutions using GenAI, traditional Machine Learning, and data-driven models.
Build and deploy
RAG , multi-agent, and protocol-based AI systems in production environments.
Integrate AI capabilities into applications using
serverless and containerized AWS architectures .
Fine-tune, optimize, and monitor models for performance, reliability, and scalability.
Develop and maintain data pipelines for model training, inference, and monitoring.
Architect and manage AI workloads on AWS, ensuring security, compliance, and cost efficiency.
Build APIs, microservices, and CI/CD pipelines to support continuous delivery and observability.
Collaborate with cross-functional teams in an agile environment and contribute to documentation and knowledge sharing.
Required Qualifications Bachelor s degree in Computer Science, AI/Machine Learning, Data Engineering, or a related field (Master s preferred).
3 years of experience building and deploying AI/Machine Learning applications in production.
2 years of hands-on experience with
AWS-based architectures
(serverless, microservices, CI/CD).
Strong experience with both
GenAI and traditional Machine Learning techniques
in real-world use cases.
Proficiency in
Python
and experience with modern AI/Machine Learning frameworks.
Technical Skills AI/Machine Learning:
PyTorch, TensorFlow, LangChain, LlamaIndex, or similar frameworks
Cloud & Infrastructure:
AWS SageMaker, Bedrock, Lambda, ECS/Fargate, API Gateway, Glue, S3
DevOps:
Docker, Git, CI/CD pipelines, Infrastructure as Code (CloudFormation)
Data:
SQL/NoSQL databases, vector databases, AWS data services
Preferred Attributes Strong foundation in data engineering and production-grade AI system design.
Excellent problem-solving, communication, and debugging skills.
Passion for applying AI to improve outcomes and operational efficiency.
Commitment to ethical AI, data privacy, and secure system design.
Ability to thrive in a fast-paced, agile, and continuously evolving environment.
Benefits:
The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan, life insurance, long-term disability insurance, short-term disability insurance, paid parking/public transportation, (paid time, paid sick and safe time, hours of paid vacation time, weeks of paid parental leave, paid holidays annually – AS Applicable).
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