Head of ML & MLOps Engineering, Fintech

This is a fully remote position, open to applicants in Mali.

📋 Description

• Create a cutting-edge machine learning platform along with the necessary discipline to support it.

• Design credit and decisioning models with thorough validation, champion/challenger testing, and emphasize explainability.

• Develop production ML serving, monitoring, reproducibility, and retraining processes.

• Establish responsible AI practices, model-risk assessments, bias checks, and explainability evaluations with an independent sign-off gate prior to production deployment.

• Construct agent-first production systems incorporating orchestration, guardrails, evaluations, and observability.

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

• Manage the ML function while taking responsibility for compute budget, personnel, and return on investment.

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

• Ensure the reliability, cost-efficiency, and latency of agent loops and graphs in production.

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

• Establish model-development standards and validation methodologies to address model-risk and regulatory scrutiny.

• Manage the ML platform that underpins decisioning services.

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

• Collaborate with Data Engineering and Credit Risk partners.

⛳️ Requirements

• Proven experience throughout the complete ML lifecycle: development, validation, deployment, monitoring, and retraining.

• Expertise in architecting agentic systems for ML, including orchestration, guardrails, evaluations in CI, human-in-the-loop checkpoints, and agent observability.

• Demonstrated experience in building and leading ML teams within regulated environments.

• Background in credit-scoring or underwriting modeling, or similar high-stakes ML applications.

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

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

• Proficient in English (B2+ level).

• Bonus: Knowledge of CCD2 and consumer credit regulations.

• Bonus: Familiarity with DORA/ICT risk.

• Bonus: Understanding IFRS 9 implications for model outputs.

• Bonus: Experience in fraud-detection ML.

• Bonus: Proficiency with Databricks/Spark.

🏝️ Benefits

• Opportunity to be part of a core leadership team.

• Build systems correctly from the outset.

• No legacy ML infrastructure to contend with.

• Experience rapid progress in a streamlined, AI-native organization.