Design machine learning models to address complex challenges

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

Implement robust machine learning infrastructures in live environments

Evaluate and analyze data to ensure model accuracy and reliability

Improve the performance and efficiency of existing machine learning models

Guide and support junior engineers while leading machine learning projects

Stay informed about the latest trends and advancements in machine learning technologies

Incorporate new data sources to boost model capabilities

Produce detailed documentation on machine learning techniques and model structures

Share technical insights and model outcomes with stakeholders and team members

A minimum of 3 years of experience in Machine Learning Engineering, with expertise in AWS technologies

Proficiency in Amazon Bedrock for the creation and deployment of machine learning solutions

Extensive background in using Amazon SageMaker to develop and manage machine learning models

Comprehensive familiarity with Amazon S3 for effective data storage and handling in machine learning projects

Advanced expertise in Python for machine learning model development

In-depth knowledge of Natural Language Processing (NLP) and its practical applications

Demonstrated capability in applying Deep Learning techniques

Competency in Prompt Engineering to enhance model interaction

Skills in implementing Sentiment Analysis for practical use cases

Understanding of effective Model Evaluation for NLP to validate performance

Fluency in English at a B2 level or higher for seamless collaboration and stakeholder communication

Understanding of other cloud platforms, including Google Cloud or Microsoft Azure

Proficiency in additional programming languages such as R or Java

Qualifications in machine learning, data science, or related disciplines