Machine Learning Engineer - Data Pipelines, Analyst

MUFG is one of the world’s leading financial groups, committed to making a difference for every client, organization, and community. They are seeking an Entry-Level Machine Learning Engineer to assist in building, testing, and deploying machine learning models that enhance data-driven decision-making.

Responsibilities

• Assist in designing, training, and validating machine learning models using structured and unstructured data
• Collaborate with data scientists, analysts, and software engineers to develop production-ready ML solutions
• Preprocess and clean large datasets to prepare for modeling
• Conduct experiments, evaluate model performance, and tune hyperparameters
• Write reusable, well-documented code in Python (or similar languages)
• Contribute to model deployment pipelines and MLOps infrastructure
• Stay current with the latest research, tools, and trends in machine learning and AI

Skills

• Bachelor's degree in computer science, Data Science, Engineering, Mathematics, Statistics, or a related field
• Strong foundational knowledge of machine learning concepts and algorithms (e.g., regression, classification, clustering)
• Proficiency in Python and ML libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch
• Familiarity with data manipulation, feature engineering, and exploratory data analysis
• Understanding of model evaluation metrics and techniques
• Good communication and teamwork skills
• Internship or project experience involving machine learning or data science
• Familiarity with version control (e.g., Git), Jupyter notebooks, and cloud platforms (e.g., AWS, GCP, or Azure)
• Exposure to LLM and Agentic AI
• Exposure to SQL and basic database concepts
• Enthusiastic about learning and growing in the field of AI/ML

Benefits

• Comprehensive health and wellness benefits
• Retirement plans
• Educational assistance and training programs
• Income replacement for qualified employees with disabilities
• Paid maternity and parental bonding leave
• Paid vacation
• Sick days
• Holidays

Company Overview