Head of ML & MLOps Engineering – Fintech

Job not on LinkedIn

🔥 58 minutes ago

🇲🇱 Mali – Remote

⏳ Contract/Temporary

🔴 Lead

🤖 Machine Learning Engineer

👻 Ghost score 14%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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InPost Group

WebsiteLinkedInAll Job Openings

10,000+ employees

🛍️ eCommerce

🚗 Transport

📦 Logistics

eCommerce • Transport • Logistics

InPost Group is Europe's leading e-commerce enablement platform, specializing in out-of-home delivery services. Founded in 1999 by CEO Rafal Brzoska, InPost provides cost-effective and environmentally friendly delivery solutions through a robust network of Automated Parcel Machines (APMs) and courier services. The company also offers pick-up drop-off (PUDO) services, enhancing convenience and efficiency for e-commerce merchants across Europe. InPost is committed to sustainability, reducing carbon emissions significantly in its delivery processes. With operations in countries like Poland, France, Benelux, the UK, and Italy, InPost continues to expand its innovative technology solutions to drive long-term growth in the e-commerce sector.

📋 Description

• Build the ML and MLOps function from zero • Build a state-of-the-art ML platform and the discipline around it • Develop credit and decisioning models with rigorous validation, champion/challenger testing and explainability • Engineer production ML serving, monitoring, reproducibility and retraining • Implement responsible AI, including model-risk, bias and explainability checks with an independent sign-off gate before production • Build agent-first production systems with orchestration, guardrails, evaluations and observability • Use a point-in-time-correct feature store and governed data • Own the ML & MLOps team from the first hire onward • Establish model-development standards and validation methodology for model-risk and regulatory scrutiny • Own the ML platform behind decisioning services • Define ownership between feature production and model consumption with Data Engineering leadership • Manage compute budget, headcount and return on investment

🎯 Requirements

• Experienced across the full ML lifecycle: development, validation, deployment, monitoring and retraining • Experienced in credit-scoring or underwriting modelling, or comparable high-stakes ML • Skilled in model-risk management and responsible-AI governance • Experienced in building and leading a team from zero • Fluent in English (B2+) • Suggested 7+ years in ML and 3+ years leading • Bonus: CCD2 and consumer-credit regulation • Bonus: DORA/ICT risk • Bonus: IFRS 9 implications for model outputs • Bonus: fraud-detection ML • Bonus: Databricks/Spark

🏖️ Benefits

• Seat at the table on a core leadership team • Build it right the first time with no legacy ML estate • Real pace in a lean, AI-native organisation • Employees can work remotely