Specialist - Machine Learning

We are seeking a talented Machine Learning Engineer to join our data science team. The ideal candidate will be responsible for developing and implementing machine learning models and algorithms that solve complex business problems. You will work closely with data scientists, software engineers, and stakeholders to deliver scalable solutions.

• Design, build, and deploy machine learning models and algorithms.
• Collaborate with data scientists to refine data features and enhance model performance.
• Optimize and improve existing machine learning models for efficiency and accuracy.
• Conduct data preprocessing, feature engineering, and data analysis.
• Monitor and maintain models in production to ensure they operate effectively.
• Document and communicate model designs and performance metrics to stakeholders.
• Stay updated on the latest industry trends and advancements in machine learning and AI.
• Participate in code reviews and contribute to a culture of continuous improvement.
• Perform statistical analysis, and train and retrain systems to optimize performance.
• Familiarity with version control systems (e.g., Git) and CI/CD practices.
• Experience with AI/GenAI.
• Experience with AWS data services (e.g., AWS EMR, AWS Glue, AWS Athena).
• Design/build and deploy API services.

Desired Candidate Profile

• Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field.
• Proven experience as a Machine Learning Engineer or in a similar role.
• Proficiency in programming languages such as Python.
• Experience with machine learning frameworks and libraries (e.g.,AWS BedRock, Amazon SageMaker, TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of algorithms, data structures, and software engineering principles.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and tools for deploying machine learning models.
• Knowledge of data manipulation and analysis tools (e.g., SQL, Pandas, NumPy).
• Excellent problem-solving skills and ability to work collaboratively in a team environment.
• Experience with deep learning and natural language processing (NLP) techniques.
• Understanding of model interpretability and explainability.