Machine Learning Engineer - Data Pipelines, Analyst

Mitsubishi UFJ Financial Group•Jersey City, NJ

17h•$82,000 - $121,000•Hybrid

About The Position

Do you want your voice heard and your actions to count? Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world’s leading financial groups. Across the globe, we’re 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world. With a vision to be the world’s most trusted financial group, it’s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career. Join MUFG, where being inspired is expected and making a meaningful impact is rewarded. The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details. Job Summary The Data Management Engineering team is embarking on a transformative journey to define, enable, and drive our data strategy. We aim to engage with partners across technology, data, business, and operations to develop and deliver business outcomes. Our team is seeking a motivated and detail-oriented Entry-Level Machine Learning Engineer to join our growing team. As a key contributor, you will help build, test, and deploy machine learning models that solve real-world problems and enhance our data-driven decision-making. This is a great opportunity for someone eager to apply their academic knowledge in a practical, fast-paced environment.

Requirements

Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or a related field
1 to 2 years of 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

Nice To Haves

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

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