[Remote] Machine Learning / Artificial Intelligence Engineer
Note: The job is a remote job and is open to candidates in USA. Finalytics AI is on a mission to make digital experiences in finance relevant, easy, and valuable. They are seeking a high-impact ML/AI Engineer to join their team and spearhead the next generation of their advanced personalization platform.
Responsibilities
- Architect Complex Data Pipelines: Integrate disparate datasets including advertising metrics, web analytics (GA4/Adobe), digital banking transactions, and third-party sources (Census, Credit Bureau)
- Build & Deploy Advanced Models: Design, train, and deploy recommender models that predict product affinity, buying intent, and user segmentation as well as learner models that understand how people and business research financial products
- Optimize & Experiment: Test models against historic data and experiment with combinations of algorithms to continually optimize for best results
- Cross-Functional Collaboration: Partner with engineering and product teams to integrate models into our SaaS platform, ensuring seamless real-time personalization
- Hypothesis-Driven Development: Analyze model performance in the wild and develop data-driven hypotheses for iterative algorithmic improvement
Skills
- Proven ML Expertise: Demonstrable experience building recommender systems using frameworks such as Collaborative Filtering, Matrix Factorization, and Reinforcement Learning
- Model Experience: Experience creating multiple models such as Collaborative Filtering, XGBoost, K-Means Clustering, and predictive modeling
- Platform Development: Strong experience integrating predictive models into live SaaS environments
- Programming: Proficiency in languages such Python, SQL, Java, or R
- Tools: Advanced experience in TensorFlow, PyTorch, JAX, Jupyter Notebooks, or R-Studio
- Bachelors degree in Statistics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years+ experience
- Experience in FinTech, banking, or credit unions
- Familiarity with credit bureau data, segmenting tools (e.g., Claritas), or advertising APIs
- Experience building agents or integrations with LLMs (e.g., via MCP or similar orchestration frameworks)
- Experience leveraging web analytics data (GA4, Piwik) for behavioral modeling
Company Overview
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