Machine Learning/AI Engineer II

Summary: Client is seeking a Senior Machine Learning Scientist to focus on the development of credit risk foundation models and associated explainability frameworks. This is a research-intensive role aimed at advancing existing machine learning approaches for credit risk. The ideal candidate will design modeling approaches leveraging large, heterogeneous financial datasets to improve credit underwriting, risk assessment, and financial inclusion. This role is perfect for candidates with strong research backgrounds who are excited about applying cutting-edge ML techniques in a real-world, high-impact fintech environment.

Responsibilities:

• Research on the development of next-generation credit foundation models, including pretraining strategies on large-scale financial datasets.
• Drive innovation in model explainability, fairness, and bias mitigation in credit decisioning systems to keep pace with transformer-based or other FM approaches.
• Develop approaches for learning from structured, semi-structured, and sequential financial data.
• Prototype and validate new modeling techniques and translate them into scalable production-ready systems.
• Collaborate with cross-functional teams across Risk, Product, Engineering, and Data Platforms.
• Define evaluation frameworks, benchmarking strategies, and experimentation pipelines.

Requirements:

• Master’s or PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field.
• 3 years of experience in machine learning, with a strong emphasis on research and model development.
• Strong background in statistical modeling, machine learning theory, and deep learning.
• Hands-on expertise in Python and ML frameworks (PyTorch preferred, TensorFlow acceptable).
• Proven experience developing ML models or algorithms, beyond standard application of existing techniques.
• Experience working with large-scale datasets and complex feature spaces.
• Strong understanding of model evaluation, validation, and experimentation methodologies.

Required Skills:

• Programming: Python, SQL
• ML Frameworks: PyTorch (preferred), TensorFlow, JAX (nice to have)
• Data & Compute: Spark, distributed training, large-scale data processing
• Cloud: AWS / GCP / Azure
• MLOps: MLflow, Kubeflow, Airflow, Docker, Kubernetes
• Version Control: Git
• Strong research mindset with the ability to translate theory into practice
• Excellent problem-solving and critical thinking skills
• Ability to communicate complex ideas to both technical and non-technical stakeholders
• Self-driven with a high degree of ownership
• Collaborative and comfortable working in cross-functional global teams

Preferred Skills:

• Demonstrated experience with experimenting with transformer or graph-based models, large-scale pretraining, or representation learning.
• Domain expertise in credit risk, lending, fintech.
• Familiarity with causal inference, time-series modeling, or sequential modeling in financial contexts.
• Experience with model interpretability and explainability (e.g., SHAP, counterfactual analysis).
• Understanding of regulatory and compliance considerations in credit modeling (guidelines, fairness, bias). #AditiConsulting # 26-04106