Design machine learning models to address complex challenges

Collaborate with multidisciplinary teams to understand business needs and identify machine learning opportunities

Deploy robust machine learning infrastructures in live environments

Conduct thorough data evaluations to ensure model precision and reliability

Improve the performance and efficiency of existing machine learning models

Provide mentorship to junior engineers and lead machine learning projects

Stay informed about emerging machine learning trends and technologies

Evaluate and integrate new data sources to enhance model capabilities

Document detailed procedures and architectures of machine learning models

Present technical insights and model outputs to stakeholders and team members

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

Proficiency in Amazon Bedrock for developing and deploying machine learning solutions

Extensive use of Amazon SageMaker for model development and management

Understanding of Amazon S3 for efficient data storage and management in machine learning projects

Advanced expertise in Python for machine learning model creation

Knowledge of Natural Language Processing (NLP) and its applications

Background in Deep Learning techniques and their practical application

Skills in Prompt Engineering to optimize model interaction

Competency in effectively applying Sentiment Analysis in real-world scenarios

Capability to execute Model Evaluation for NLP to ensure performance metrics are met

Proficiency in English at a B2 level or higher for effective collaboration and communication

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

Qualifications in additional programming languages like R or Java

Background in obtaining certifications in machine learning, data science, or related disciplines