Senior ML Engineer

Quick Facts

• Role: Senior ML Engineer (machine learning + statistics)
• Work model: 100% remote within Poland; regular team meetings in Warsaw
• Projects: commercial and research & development in one team

Description

Design, build, and validate machine learning models for risk on tabular data as well as on satellite and spatial data. You will create reusable pipelines for training and evaluation and deploy models to production together with engineers. You’ll also work on multi-criteria pricing optimization driven by many parameters.

Responsibilities

• Build and validate baseline, GLM, and gradient-boosting models with time-aware validation and calibration
• Develop repeatable training/evaluation pipelines and implement deployments to production
• Participate in multi-criteria optimization for pricing decisions
• Set technical standards, perform code reviews, and review other team members’ models
• Present models live with client experts (in English)
• Work in both commercial and research & development projects

Requirements

• Senior experience: independently run an ML project from problem definition to production deployment
• Very strong Python for production use (testing, version control, code review) and strong SQL
• Solid statistics fundamentals (correct target definition and exposure, detect data leakage, validate with time-aware splits)
• Practical experience with GLM and boosting models
• Fluent English for technical discussions
• Ability to turn results into actionable recommendations and be explicit when data is insufficient

Benefits

• Employment contract (full-time) or B2B cooperation with compensation stated in the posting
• 100% remote work from anywhere in Poland with regular Warsaw team meetings
• Mix of commercial and R&D projects in the same team
• AI tools (e.g., Claude Code) as part of daily technical work
• Opportunity to influence how the team works by joining early

Recruitment process

• Short introductory call (financial expectations, notice period, a few minutes in English) plus discussion of one successful project
• Technical interview / practical assignment based on a sample problem