AI/ML Engineer
About The Role
Chime’s AI/ML Trust & Safety team is building models, insights, and decisioning systems that help protect millions of members while enabling safe, reliable financial progress. We are looking for an AI/ML Engineer who is growing strong technical depth in machine learning, experimentation, and analytical problem solving, with an interest in applying those skills to trust, safety, and risk challenges across Chime.
Responsibilities
- Contribute to the design and implementation of training pipeline components for AI/ML models that support Chime’s risk decisioning systems.
- Develop, test, and iterate on model features within clear requirements and with support from senior team members.
- Support offline model evaluation and contribute to online experiment analysis to understand performance, tradeoffs, and member impact.
- Write modular, testable, and maintainable code following engineering best practices.
- Collaborate with Product Managers, Engineers, and Risk teams to translate model findings into clear recommendations and measurable member impact.
- Contribute to production-facing model workflows, including model training, tuning, inference, and monitoring.
- Contribute to projects that apply modern AI/ML methods, such as generative AI, sequence models, and automation workflows, to improve Risk decisioning.
Requirements
- 1–2 years of experience in applied data science or AI/ML engineering, including relevant internship, academic, or project experience.
- Working knowledge of machine learning fundamentals, including feature development, model training, validation, tuning, and evaluation.
- Familiarity with cloud platforms, preferably AWS, orchestration tools, and version control.
- Familiarity with offline model evaluation, experimentation, and model performance tradeoffs.
- Ability to communicate analyses and model findings clearly, clarify requirements, and collaborate effectively with technical and non-technical partners.
Qualifications
- Nice to have exposure to production ML workflows, including inference, monitoring, retraining, orchestration, model deployment.
- Experience using AI-assisted development tools such as Cursor, Claude Code, or similar tools.
- Exposure to deep learning methods, such as embeddings, sequence models, representation learning, or behavioral modeling.
Skills
- Strong understanding of machine learning algorithms and techniques.
- Experience with Python, R, or other programming languages commonly used in data science and machine learning.
- Knowledge of data preprocessing, feature engineering, and model selection.
- Experience with cloud platforms like AWS, Google Cloud, or Azure.
- Proficiency in version control systems such as Git.
- Experience with data visualization tools like Matplotlib, Seaborn, or Tableau.
- Experience with statistical analysis and hypothesis testing.
- Experience with cloud-based machine learning frameworks like TensorFlow, PyTorch, or Scikit-Learn.
- Experience with data pipelines and ETL processes.
- Experience with cloud-based machine learning frameworks like TensorFlow, PyTorch, or Scikit-Learn.
Benefits
The base salary offered for this role and level of experience will begin at $125,000.00 and up to $173,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.
Pay
The base salary offered for this role and level of experience will begin at $125,000.00 and up to $173,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.
Schedule
In this role, you can expect to work 4 days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location.