Overview
On Site
Depends on Experience
Full Time
Skills
cloud
aws
ai
Job Details
Independent candidate only.
At least ten or more years of experience performing the
functions associated with this labor category
Bachelor's or Master's degree in Computer Science, Artificial
Intelligence, Machine Learning, or equivalent work experience.
Proven experience in Generative AI, data engineering, AWS AI,
and AWS data services.
Proficiency in programming languages such as Python, Java, or
similar.
Experience with data engineering concepts and tools
Experience in Terraform, Dockers, Kubernetes, and/or Gitlab
Understanding of data governance and security principles
Hands-on experience with DevSecOps and CI/CD practices
Excellent problem-solving and analytical skills
Ability to work independently and as part of a team
Familiarity with government cloud deployment
regulations/compliance policies such as FedRAMP, FISMA, etc.
Experience with specific generative AI models like GPT, Llama,
Claude, and others from HuggingFace
Knowledge of deep learning frameworks such as PyTorch and
Transformer
Contributions to open-source AI projects or communities
Certifications in AWS AI or machine learning
Capabilities
Builds next-generation AI & analytics framework developed
on a group of core technologies.
Utilize Generative AI techniques to create innovative
solutions for business challenges.
AWS AI Services: Leverage AWS AI services like Amazon
Bedrock, SageMaker, Comprehend, Rekognition, Transcribe
to accelerate AI development and deployment.
Lead multi-functional teams in designing and implementing
cloud-based data and AI solutions.
Ensure data pipelines are scalable, secure, and repeatable.
AWS Data Services: Utilize AWS data services like Amazon
S3, Amazon Redshift, and Amazon DynamoDB to store,
manage, and process large-scale datasets.
Collaborate with stakeholders to understand business
requirements and turn data into insights.
Develop and maintain cloud infrastructure, including data
lakes, warehouses, and analytics platforms.
Implement data governance and security best practices.
DevSecOps: Contribute to a DevSecOps culture by adhering
to standard methodologies for secure software development
and deployment.
CI/CD: Automate AI model development, testing, and
deployment using CI/CD pipelines.
Acts as an inspiring leader, with an outstanding perspective,
and promotes the adoption of new software and technology
across the company.
Works on multiple projects as a technical team member
driving business requirements end to end
Takes end to end accountability of all data products and
solutions.
Conducts training bootcamps and cross-training workshops
for internal collaborators and customers.
Certifications in AWS
AI or Machine Learning
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