Job Description
Job Description
Title: AI/ML Engineer
Reports to: Chief Technology Officer
Location: US Remote
About the Company
At BMG Money, we help people solve unexpected financial problems affordably. Our team members draw from many years of experience at leading banks, fintechs, law firms, and governments. We all share one vision—we help employees borrow and improve their financial quality of life. BMG embraces innovation, is committed to quality, and is unafraid to challenge the status quo.
Job Summary
BMG Money is seeking an exceptional AI/ML Engineer to revolutionize fintech with us. Our fast-growing team is at the forefront of leveraging artificial intelligence to transform financial services, making them smarter, faster, and more accessible for everyone. As an AI/ML Engineer, you'll play a key role in building intelligent systems that power real-time decisions, risk assessments, fraud detection, customer experiences, and more. You'll work with diverse data, scalable architectures, and cutting-edge models that help us stay one step ahead in a dynamic market.
Key Responsibilities
- Design, train, and fine-tune machine learning and deep learning models that tackle critical fintech challenges—including credit scoring, risk modeling, and recommendation systems.
- Ensure accuracy, explainability, and robustness for all production-deployed models.
- Collect, clean, and process large, high-dimensional financial datasets (both structured and unstructured).
- Conduct exploratory data analysis (EDA) to identify hidden patterns, anomalies, and strategic opportunities for automation or insight.
- Collaborate closely with engineering teams to seamlessly deploy models into scalable microservices or APIs.
- Own the full ML lifecycle—from initial experimentation and validation to ongoing monitoring and retraining.
- Continuously research and integrate the latest advancements in AI, Large Language Models (LLMs), MLOps, and broader fintech AI trends.
- Rapidly prototype new approaches and conduct A/B tests to validate their real-world impact.
- Partner with product, fraud, engineering, and compliance teams to ensure AI solutions are fully aligned with business strategy and regulatory requirements.
- Participate actively in code reviews and contribute to a healthy, high-performing engineering culture.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
- 3+ years of hands-on experience building, deploying, and maintaining production-grade ML models, ideally within fintech, banking, or other high-risk, regulated domains.
- A deep understanding of machine learning techniques, including classification, regression, clustering, and time series forecasting, coupled with the ability to select and apply the right models for complex financial problems.
- Strong Python skills and deep knowledge of key ML/DL libraries (e.g., Scikit-learn, PyTorch, TensorFlow, XGBoost).
- Direct experience working with financial data, KPIs (Key Performance Indicators), or compliance-sensitive systems is a significant advantage.
- Experience with cloud platforms (e.g., GCP, AWS, Azure) and containerized environments (e.g., Docker, Kubernetes).
- Comfortable with Git, collaborative workflows, and agile development methodologies.
Preferred Qualifications
- Direct experience with fraud detection, credit scoring, or real-time decision-making systems.
- Familiarity with Large Language Models (LLMs) or Natural Language Processing (NLP) use cases in fintech (e.g., document parsing, sentiment analysis, chatbot optimization).
- Knowledge of specialized MLOps tools (e.g., MLflow, Vertex AI Pipelines, SageMaker Studio).
- Contributions to open-source projects or relevant publications in ML/AI.
- A strong understanding of data privacy, model explainability (XAI), and fairness principles as applied to financial AI applications.