Machine Learning Engineer

Rapideagle is seeking a dynamic and innovative Machine Learning Engineer to join their forward-thinking data science team. In this role, you will leverage cutting-edge AI and machine learning frameworks to develop, train, and deploy sophisticated models that solve complex business challenges.

Responsibilities:

• Design, develop, and optimize machine learning models using frameworks such as TensorFlow, Spark MLlib, and other AI tools
• Implement unsupervised learning algorithms to uncover hidden patterns within large datasets
• Collaborate with cross-functional teams to translate business needs into scalable data solutions and predictive models
• Conduct data mining, feature engineering, and model training activities utilizing SQL, Python, R, and SAS
• Deploy machine learning models into production environments with a focus on model performance, scalability, and reliability using AWS cloud services
• Develop ETL pipelines with Talend or Bash scripts to extract, transform, and load data from diverse sources including Hadoop-based big data systems
• Design database schemas optimized for analytics and ensure efficient data storage using database design principles
• Integrate natural language processing techniques for text analysis and linked data applications to enhance semantic understanding
• Monitor model performance continuously and refine algorithms through iterative testing to improve accuracy and efficiency
• Support the deployment of AI solutions through containerization and orchestration tools to facilitate seamless integration into existing systems

Requirements:

• Proven experience in developing machine learning models with frameworks such as TensorFlow or similar platforms
• Strong programming skills in Python, Java, C, and Bash (Unix shell)
• Hands-on experience working with big data technologies including Hadoop, Spark, and Hadoop ecosystem tools like Hive or Pig
• Familiarity with cloud computing platforms such as AWS for scalable model deployment and data storage solutions
• Knowledge of natural language processing (NLP), linked data concepts, and AI techniques for semantic analysis
• Experience designing databases optimized for analytics workloads along with proficiency in SQL for complex querying
• Demonstrated ability to work on cross-disciplinary teams in a fast-paced environment while managing multiple projects simultaneously
• Background in data mining, statistical analysis, and analytics tools like Looker or VBA is highly desirable
• Understanding of quantum engineering principles as they relate to advanced computational methods is a plus but not mandatory