Machine Learning Engineer

Job Description – Duties:

• Collaborate with data scientists, software engineers, and Dev Ops 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

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• Minimum of 5-7 years of experience in ML Ops, Dev Ops, or related roles
• Strong knowledge of AWS services and tools related to ML Ops, such as Sage Maker, Step Functions, Lambda, and Cloud Formation
• 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

• Knowledge of machine learning concepts, algorithms, and frameworks.
• Knowledge of software engineering principles and best practices, such as version control, continuous integration, and agile development methodologies.
• Strong understanding of data analysis and data manipulation techniques.
• Ability to design and implement scalable, secure, and fault-tolerant ML Ops pipelines on AWS.
• Ability to analyze and interpret data to identify patterns, trends, and anomalies, using advanced data manipulation techniques.
• Outstanding communication skills (verbal, written, visualization, and listening).
• Self-starter who can work independently as well as in a team setting.
• Hands-on technologist with the ability to help drive the strategy and mentor others.
• Giving and receiving effective feedback across all interactions.
• Interest in understanding customer perspectives to aid in the development of the right solution.
• Interest in understanding business needs to aid in developing solutions that are right for the broader organization.