Architect and engineer machine learning models to address complex challenges

Work alongside multidisciplinary teams to grasp business needs and explore machine learning opportunities

Deploy robust machine learning infrastructures in live environments

Perform thorough data evaluations and tests to validate model precision and dependability

Enhance the performance and efficiency of current machine learning models

Mentor junior engineers and lead machine learning initiatives

Keep abreast of emerging machine learning trends and technologies

Assess and assimilate new data sources to augment model capabilities

Record detailed documentation of machine learning procedures and model structures

Communicate technical insights and model results to stakeholders and team members

At least 3 years of professional experience in Machine Learning Engineering, with a focus on AWS technologies

Demonstrated proficiency with Amazon Bedrock for the development and deployment of machine learning solutions

Comprehensive experience in utilizing Amazon SageMaker to develop and manage machine learning models

Profound understanding of Amazon S3 for effective data storage and handling in machine learning projects

Advanced proficiency in Python for machine learning model development

Specialized knowledge in Natural Language Processing (NLP) and its applications

Extensive experience with Deep Learning techniques and their implementation

Skilled in Prompt Engineering to improve machine learning model interaction

Adept in implementing Sentiment Analysis in practical scenarios

Ability to perform effective Model Evaluation for NLP to verify model performance

Fluent in English at a B2 level or higher, necessary for efficient team collaboration and communication with stakeholders

Experience with other cloud platforms such as Google Cloud or Microsoft Azure

Knowledge of additional programming languages like R or Java

Relevant certifications in machine learning, data science, or associated fields