Roles and Responsibilities
Deploy and scale distributed systems in a cloud environment (internal Cloud and AWS implementations)
Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
Collaborate with cross-functional teams including data scientists, product managers, and software engineers to solve complex problems
Ability to gain knowledge in ML Engineering with Large Language Models and run them efficiently (Managed LLMs and self-hosted LLMs)
Build services focused on domains.
Required qualifications, capabilities, and skills
Strong knowledge with modern back-end technologies
Experience on usage and management of data bases, preferable on con MongoDB and Redis
Formal training or certification on software engineering concepts and 3+ years applied
Experience
Exposure and knowledge of cloud technologies,
Experience deploying applications Kubernetes
Strong knowledge and experience in CI/CD pipelines and tools such as Jenkins, Spinnaker, GIT/Bitbucket, Terraform and Dockers,
Strong experience with software engineering best practices, such as version control, testing, and continuous integration and deployment
Preferred qualifications, capabilities, and skills
Programming skills in Python and experience with machine learning libraries such as TensorFlow, PyTorch, or scikit-learn
Familiarity with statistical and machine learning techniques, including supervised and unsupervised
Bachelor's Degree in Computer Science or relatable field.
Streaming technologies such as Kafka
Knowledge and experience with Grafana.