MLOPs Engg

Job Title- MLOps Engineer

We are seeking an experienced MLOps Engineer specializing in AWS to architect, implement, and maintain robust machine learning operations infrastructure. This role is crucial in bridging the gap between data science and production deployment, ensuring seamless delivery of ML solutions at scale. The ideal candidate will be responsible for building and maintaining scalable, automated ML pipelines, implementing CI/CD practices, and optimizing cloud infrastructure for ML workloads. They will work closely with data scientists and software engineers to streamline the model deployment process, establish monitoring systems, and ensure high availability of ML services. Essential

Experience Required

Total: 5 6 years with 3+ years in AWS Proven HandsOn experience in

AWS cloud infrastructure management

MLOps pipeline development

Container orchestration

CI/CD implementation

Production system monitoring

Infrastructure as Code (Terraform/CloudFormation) Desired Skills Technical Skills

- AWS Services expertise

SageMaker and its components

Container technologies (Docker, Kubernetes)

Python programming - Git and version control - CI/CD tools (Gitlab,Jenkins, GitHub Actions) MLOps Knowledge

ML deployment patterns - Model serving architectures - Feature stores - Experiment tracking - Model monitoring

A/B testing frameworks - Development Tools - Kubeflow - MLflow - System architecture design - Performance optimization - Security implementation

Soft Skills- - Problem solving ability - Communication skills - Team collaboration - Self motivated learning

Agile methodology

Additional Skills

Understanding of ML/DL concepts

Experience with microservices architecture

Knowledge of Fast API

Familiarity with logging and tracin tools

Undertanding of data privacy and compliance