Our client is a performance-driven digital marketing provider specializing in lead generation and conversion optimization. They help businesses grow by combining data-based insights, advanced marketing tools, and high-performing funnels across multiple industry verticals.
Role Summary
Develops, trains, and evaluates ML models — especially tabular, predictive, and ranking models — and contributes directly to production-first modeling efforts across the funnel.
Minimum Requirements (Must Have)
- Strong hands-on experience with tabular ML models (XGBoost, LightGBM, CatBoost, logistic regression, etc.)
- Proven experience with data wrangling, feature engineering, and dataset preparation
- Experience training, tuning, and evaluating models at scale
- Solid understanding of model validation
- Strong Python skills and familiarity with ML libraries
- Ability to translate hypotheses into measurable experiments
- Experience working closely with data engineering pipelines
Preferred Qualifications (Nice to Have)
- Experience with inference engineering: packaging models, building inference endpoints, optimizing latency
- Exposure to model monitoring: drift, data quality checks, performance monitoring
- Experience with containerization (Docker) and serving frameworks (FastAPI, Flask, TorchServe, Bento, etc.)
- Experience deploying ML models in production environments
- Prior experience with ranking, scoring, or optimization models
We offer:
- Remote-first model of work;
- Cooperation under the FOP model/B2B contract;
- Paid vacation (18 working days per year);
- Paid sick leaves (10 days per year);
- Paid medical insurance after the probation period;
- English-speaking clubs.
