ML Engineer
We’re looking for an ML Engineer
- Work arrangement: Fully remote
About the role
Project details
Engagement: full-time (40h/week)
Start: 30.11.2026
Contract length: 12 months
English: min. B2+
Requirements
5+ years of hands-on ML engineering in Python, with ownership of deployed models and reliable production code,
experience integrating predictions with external platforms via API so they trigger automated actions (campaign optimization, recommendations, pricing),
strong SQL and BigQuery skills for feature engineering, data validation and reproducible transformations,
hands-on experience running ML workloads on GCP: Vertex AI, Pub/Sub, Cloud Run, Composer/Airflow,
gradient boosting models (LightGBM, CatBoost, XGBoost), including tuning and evaluation against business-relevant metrics,
ability to calibrate predictions and assess how model errors affect downstream decisions.
Requirements
Strongly preferred
entity resolution / identity resolution,
propensity, churn/retention, segmentation or LTV modeling in e-commerce or DTC,
server-side conversion tracking (Google Enhanced Conversions, Meta Conversions API),
Bayesian methods and probabilistic customer models (BG/NBD, Gamma-Gamma).
Nice to have
experimentation, causal inference or bandit methods applied to marketing,
Docker, Terraform, CI/CD for pipelines,
familiarity with AI tools (e.g. Cursor, Claude Code).
How it works for you
Apply once
Pick an open role or send a general application. Your CV is enough to start.
Record your interviews
Answer questions on camera when it suits you: first about how you work, then on your stack, with a short timed test.
A short live call
Once your interviews pass, we meet you on a quick video call.
Matched to client work
We put you forward for every role that fits, not only the one you applied to, and tell you when there is no current match.
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