Machine Learning Engineer 1 or 2

 This position will help advance the  Data Management and Data Analytics strategy by increasing our capabilities to deliver rapidly, efficiently while providing excellent value for the organization.

The ML Engineer will work with stakeholders – both business and IT to be responsible for designing, developing, and implementing machine learning models and algorithms to solve complex problems and enhance our products and services. Your expertise will be critical in driving innovation and improving user experiences.

Job Responsibilities:

• Model Development: Collaborate with cross-functional teams to identify and understand business challenges and translate them into machine learning tasks. Design, build, and optimize machine learning models and algorithms for various applications.

• Data Processing: Work with large datasets, cleaning and preprocessing them for model training and validation. Ensure data quality and integrity to enable accurate model predictions.

• Environment Setup: Set up and maintain machine learning environments, including frameworks such as TensorFlow, PyTorch, or Scikit-learn, and cloud-based platforms like Azure.

• Model Training and Evaluation: Implement machine learning experiments and conduct rigorous testing and evaluation to measure model performance and identify opportunities for improvement.

• Deployment and Integration: Collaborate with software engineers to deploy machine learning models into production environments and integrate them with existing systems.

• Continuous Improvement: Stay up-to-date with the latest developments in the field of machine learning, and explore new methodologies and technologies to enhance our solutions.

• Documentation and Communication: Document your work thoroughly, including model architectures, methodologies, and results. Present findings and insights to stakeholders in a clear and understandable manner.

Technical Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.

• Proven experience in developing and deploying machine learning models and algorithms.

• Strong proficiency in Python and popular machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn).

• Familiarity with cloud-based platforms for model deployment and management (e.g., AWS, GCP, Azure).

• Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.

• Ability to work effectively in a collaborative, cross-functional team environment.

• Strong problem-solving skills and a passion for tackling complex challenges.

• Excellent communication and presentation skills.

Preferred Qualifications:

• Experience with big data technologies such as Hadoop, Spark, or similar.

• Knowledge of deep learning architectures and techniques.

• Previous experience in natural language processing (NLP) or computer vision projects.

• Understanding of version control systems like Git.