Head of ML & MLOps Engineering – Fintech Engineering

This is a fully remote position, open to applicants in Mali, +1 more country.

📋 Description

• Develop a cutting-edge ML platform along with the associated discipline.

• Create models that are backed by business cases and quantifiable financial results.

• Design credit and decision-making models that include thorough validation, champion/challenger testing, and transparency.

• Engineer the production ML serving, monitoring, reproducibility, and retraining processes.

• Implement responsible AI practices, model-risk assessments, bias checks, and ensure explainability with independent validation prior to production.

• Construct production agent systems equipped with orchestration, guardrails, evaluations, and observability features.

• Develop a point-in-time-correct feature store.

• Oversee the ML & MLOps function, managing the compute budget, staffing, and return on investment.

• Manage agentic model iteration, monitoring, and observability linked to the feature store.

• Take responsibility for the reliability, cost, and latency of production agent loops and graphs.

• Recruit and lead the ML & MLOps team starting from the initial hire.

• Establish model-development standards and validation methodologies to meet model-risk and regulatory requirements.

• Manage the ML platform that supports decision-making services.

• Define roles and responsibilities between feature production and model consumption in collaboration with Data Engineering and the Director.

• Collaborate with Data Engineering and Credit Risk partners.

⛳️ Requirements

• Proficient across the entire ML lifecycle: development, validation, deployment, monitoring, and retraining.

• Experienced in designing agentic systems for ML, including orchestration, guardrails, continuous integration evaluations, human-in-the-loop checkpoints, and agent observability.

• Proven track record in building and leading ML teams within regulated environments.

• Experience with credit-scoring or underwriting modeling, or similar high-stakes ML applications.

• Knowledgeable in model-risk management and responsible AI governance.

• Experienced in building and leading a team from the ground up.

• Proficient in English (B2+ level).

• Bonus: Familiarity with CCD2 and consumer-credit regulation; DORA/ICT risk; IFRS 9 implications for model outputs; fraud-detection ML; Databricks/Spark.

🏝️ Benefits

• Opportunity to be part of a key leadership team.

• Chance to get it right the first time with no existing legacy ML infrastructure.

• Experience a dynamic pace within a lean, AI-native organization.