Description

You will design and architect large-scale systems and ML infrastructure in the cloud.

Responsibilities

• Develop ML infrastructure for DataOps, MLOps, and DevOps using AWS.
• Build automated CI/CD pipelines for deploying ML models to production.
• Construct data pipelines to collect, train, and evaluate models using distributed processing frameworks.
• Manage applications in the cloud using Infrastructure as Code (IaC) principles.
• Implement feature engineering and machine learning algorithms, including NLP word embeddings.

Required Skills

• 5+ years of experience in system design and architecture.
• Proficiency in Python ML ecosystems including NumPy, Pandas, scikit-learn, TensorFlow, or PyTorch.
• Hands-on experience with AWS services such as EC2, EMR, EKS, S3, and SageMaker.
• Experience with distributed data processing using Apache Spark or Snowflake.
• Strong knowledge of Docker, Kubernetes, and AWS CloudFormation.
• Ability to use CI/CD tools like Jenkins, GitHub, and Artifactory.
• Experience with Object Oriented Programming and functional scripting in Node.js or Unix.
• Bachelor’s or Master’s Degree in Engineering, Computer Science, or a related technology field.

Key Skills

Education

Any Graduate