Senior ML Engineer - Real-Time AdTech Optimization (Remote)

Sigma Software

Województwo mazowieckie

Remote

PLN 240,000 - 360,000

Full time

4 days ago
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Job summary

Sigma Software is seeking a Senior Machine Learning Engineer to join a dedicated team building a predictive, real-time decisioning platform for programmatic advertising. You’ll work on production-grade models, scalable training pipelines, and model orchestration within a live ad exchange, with fully remote collaboration across distributed teams.

Key focus areas include building and deploying high-impact ML solutions, monitoring model quality, and optimizing business outcomes in a fast-paced

Qualifications

  • 6+ years of combined commercial experience in Data Science and ML Engineering, including at least 2 years in each area.
  • ,

Responsibilities

  • Build and validate predictive models for ad exchange with real-time requirements.
  • Design and implement offline evaluation using inverse propensity scoring.
  • Define exploration strategies and propensity logging for evaluation.
  • Calibrate models for advertisers while monitoring ranking and calibration.
  • Develop and operate scalable training orchestration pipelines.
  • Maintain model registry workflows with lineage and promotions.
  • Implement per-advertiser model instances with namespace separation.
  • Own model publishing pipelines with SLOs and fallback procedures.
  • Run shadow deployments and champion/challenger experiments.
  • Monitor drift, latency, and reproducibility in production.
  • Prepare technical docs and support knowledge transfer.

Skills

Python
SQL
XGBoost
LightGBM
CatBoost
Kubernetes
Docker
GCP
MLflow
Kubeflow
Airflow
Argo
Terraform
Data modeling
Experimentation
English

Tools

MLflow
Kubeflow
Airflow
Argo
Kubernetes
Docker

Job description

Sigma Software is seeking a Senior Machine Learning Engineer to join a dedicated team building a predictive, real-time decisioning platform for programmatic advertising. You’ll work on production-grade models, scalable training pipelines, and model orchestration within a live ad exchange, with fully remote collaboration across distributed teams.

Key focus areas include building and deploying high-impact ML solutions, monitoring model quality, and optimizing business outcomes in a fast-paced

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