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.