Sr Machine Learning Engineer

Collaborate with data scientists, software engineers, and DevOps teams to develop and deploy ML models
Build, test, and deploy ML Ops pipelines on AWS
Manage and monitor production ML systems to ensure optimal performance, reliability, and scalability
Design and implement automated workflows for data cleaning, feature engineering, model training, and model deployment
Develop and maintain documentation for ML Ops processes and procedures
Continuously improve ML Ops pipeline performance and efficiency
Troubleshoot and resolve issues related to ML model performance, data quality, and infrastructure
Requirements:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Minimum of 5-7 years of experience in ML Ops, DevOps, or related roles
Strong knowledge of AWS services and tools related to ML Ops, such as SageMaker, Step Functions, Lambda, and CloudFormation
Hands-on experience building and deploying ML models in production using AWS
Proficiency in Python and/or other programming languages commonly used in ML, such as R, Java, or Scala
Familiarity with containerization technologies such as Docker and Kubernetes
Excellent problem-solving skills and attention to detail
Ability to work independently as well as in a team environment
Strong communication skills and ability to explain technical concepts to non-technical stakeholders