W skrócie
- Zadania: Buduj platformę ML, która generuje zyski i spełnia wymogi regulacyjne.
- Firma: InPost - innowacyjna firma fintechowa z dynamicznym zespołem.
- Benefity: Atrakcyjne wynagrodzenie, możliwość pracy zdalnej i rozwój zawodowy.
- Pozostałe informacje: Praca w zespole kierowniczym z możliwością budowania od podstaw.
- Dlaczego ta praca: Zyskaj wpływ na modele ML, które mają realną wartość finansową.
- Kwalifikacje: 7+ lat doświadczenia w ML, 3+ lata w roli lidera.
Przewidywane wynagrodzenie mieści się w przedziale 123750 - 151250 zł za rok.
Head of ML & MLOps Engineering - Fintech Engineering
Contract Build ML that makes money and stands up to a regulator.
We are building a scale-up inside In Post, and AI will flow through it.
You would join the core Data & AI leadership team and build the ML and MLOps function from zero, with the In Post executive team backing it.
Our word is extreme ownership : you own a model from first idea to its profit and loss impact.
The mission Build a state-of-the-art ML platform and the discipline around it.
Models with a price tag.
Every model has a business case and a measurable monetary outcome. Credit and decisioning models built with rigorous validation, champion/challenger testing and explainability. A production ML platform.
Serving, monitoring, reproducibility and retraining are engineered, not improvised. Responsible AI, built in.
Model risk, bias and explainability checks, with an independent sign-off gate before anything reaches production. Agent-first systems.
Agents are production components with orchestration, guardrails, evals and observability. Models on governed data.
You build on a point-in-time-correct feature store, not around it. This is a business function.
Every model carries monetary value, and you will run the function that way: compute budget, headcount and return on investment.
What you'll own The ML & MLOps team, from your first hire onward.
Model-development standards and the validation methodology that stands up to model-risk and regulatory scrutiny.
The ML platform behind decisioning services.
A clear ownership line between feature production (data engineering) and model consumption, set together with the Head of Data Engineering and the Director.
You are A leader who loves data and loves building systems around it.
Hands-on when needed , especially with AI on board.
You understand the model, the pipeline and the serving layer.
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+). [add years of experience: suggest 7+ years in ML, 3+ leading] Bonus CCD2 and consumer-credit regulation
- DORA/ICT risk
- IFRS 9 implications for model outputs
- fraud-detection ML
- Databricks/Spark.
Why this one Seat at the table on a core leadership team. Build it right the first time.
No legacy ML estate. Models that matter.
Your work decides real money, not a dashboard. Real pace.
A lean, AI-native organisation.
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Head of ML & MLOps Engineering in Warsaw – pracodawca: InPost
InPost to doskonały pracodawca, który oferuje wyjątkowe możliwości rozwoju w dynamicznym środowisku e-commerce. Pracując jako Senior Data Developer, będziesz miał realny wpływ na podejmowanie decyzji strategicznych, a także możliwość współpracy z międzynarodowym zespołem ekspertów. Nasza kultura pracy sprzyja innowacjom i eksperymentowaniu z nowymi technologiami, co czyni naszą firmę atrakcyjnym miejscem dla osób poszukujących satysfakcjonującej kariery.
