Overview
Hybrid
Depends on Experience
Full Time
Skills
Amazon SageMaker
Amazon Web Services
Communication
Artificial Intelligence
Cloud Architecture
Continuous Integration
Deep Learning
DevOps
Docker
Generative Artificial Intelligence (AI)
Prompt Engineering
PyTorch
Python
TensorFlow
Machine Learning (ML)
Data Engineering
Financial Services
Kubernetes
Job Details
Job Responsibilities
REQUIREMENTS:
7+ years of experience in financial services, with tangible AI and machine learning projects.
- Extensive experience in designing and implementing AI/ML platforms and architectures.
- Experience leading large data & AI transformation projects
- Proficiency in AWS services, including Amazon SageMaker, Amazon Bedrock.
- Strong architecture & development skills in Python, Java, or other relevant languages.
- Familiarity with cloud architecture and deployment strategies.
- Experience leading development team and Prompt Engineering, etc.
- Strong communication skills, both written and verbal.
PREFERRED: - Experience with AWS AI and ML services, including Amazon Rekognition, Amazon Comprehend, and Amazon Lex, etc.
- Knowledge of data engineering and ETL processes.
- Experience with containerization technologies such as Docker and Kubernetes.
- Understanding of data privacy and security best practices.
NICE TO HAVE: - Experience with generative AI models and frameworks such as GPT, GANs, or other deep learning models.
- Knowledge of big data technologies and tools such as Hadoop, Spark, or Kafka.
- Experience with AI/ML tools and libraries such as TensorFlow, PyTorch, or scikit-learn.
- Strong understanding of DevOps practices and CI/CD pipelines.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.