POSITION SUMMARY AND PRIMARY RESPONSIBILITIES

Position Summary:

We are seeking an experienced Senior Machine Learning Engineer to join our dynamic and innovative team. As a Senior Machine Learning Engineer, you will play a key role in developing and implementing machine learning models to solve complex business problems. You will collaborate with cross-functional teams to understand requirements as well as deliver scalable and efficient ML solutions.

Responsibilities:

• Developed and implemented advanced machine learning models to address specific business challenges
• Explore the data and identify differences in data distribution that could impact performance when deployed
• Train, evaluate, and fine-tune machine learning models using appropriate frameworks and tools
• Work with data scientists to implement data preprocessing and feature engineering infrastructure to improve model performance
• Optimize machine learning models for scalability and efficiency, considering real-time and batch processing requirements
• Ensure code quality, maintainability, and documentation standards are met. Write clear and concise technical documentation
• Stay updated on the latest advancements in machine learning and contribute to the research and innovation within the field
• Propose and implement improvements in existing model development
• Work closely with data scientists to define collection events and data transformations needed to drive personalized learning
• Work closely with Product Owners to understand potentials and limitations of AI models developed and deployed
• Provide quidance and mentorship to junior members of the team
• Adhere to ethical standards and comply with data laws and regulations applicable to the job function
• Clearly communicate findings to senior leadership

REQUIRED SKILLS

• Experience with Python-based AI/ML frameworks, Java, and/or R
• Experience with ML frameworks (like Keras, PyTorch, Tensorflow) and libraries (like scikit-learn)
• Experience working with large datasets, handling data proprocessing tasks, and exploring data to identify patterns and insights
• Knowledge and practical application of statistical analysis and mathematical modeling concepts and principles
• Proficiency in cloud services like SageMaker, S3, EC2, Azure Machine Learning
• Ability to containerize machine learning applications for portability and reproducibility
• Understanding of container orchestration for managing and scaling containers in a cloud environment
• Knowledge of serverless computing for executing code without managing the underlying infrastructure
• Experience with object storage for managing large datasets
• Knowledge of databases for storing and retrieving data
• Ability to provision and manage virtual machines for machine learning tasks
• Monitoring and logging tools for tracking the performance and health of models
• Understanding of identify and access management for securing cloud resources
• Integration of machine learning workflows into CI/CD pipelines for automated deployment
• Ability to optimize costs associated cloud resources
• Hands on experience with cloud-based ML services for model training, deployment, and management
• Understanding of cloud networking for secure and efficient communication between services
• Proficiency in version control for collaboration and code management
• Excellent communication skills
• Ability to work effectively in a cross-functional team

POSITION SPECIFICATIONS -

Education, Certifications, or Special Licenses:

Master’s Degree or Ph.D. in Computer Science, Machine Learning, Applied Mathematics, Engineering or a related field

3 to 5 years of training or experience in AI/ML algorithm development

Experience in technology enhanced learning solution research and development

Other Requirements (Specialized skill sets, behavioral/technical):

• Experience with Python-based AI/ML frameworks, Java, and/or R
• Experience with ML frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
• Knowledge and practical application of statistical analysis and mathematical modeling concepts and principles
• Excellent communication skills
• Ability to work effectively in a cross-functional team