Applied AI & MLOps Lead — Senior ML Engineer

Salve.Inno Consulting; Warszawa; On-site; PLN 210,000 - 330,000; Full time

Benefits offered by this job

Competitive remuneration

Professional development programmes

International environment

Team events

Birthday and loyalty benefits

Job summary

Salve.Inno Consulting is seeking a Senior Machine Learning Engineer to own end-to-end production AI solutions, from design to deployment and monitoring, with a focus on reliability and business impact. You will lead ML lifecycle, MLflow, CI/CD pipelines and MLOps practices, collaborating with Data Engineering, Product, Risk and Commercial teams to deliver scalable, explainable models and measurable value.

The role requires 5–8+ years of experience, advanced Python, Spark, MLflow and strong

Qualifications

• 5-8+ years of professional experience developing, deploying and maintaining ML models in production.
• Advanced Python programming skills and strong software engineering fundamentals.
• Solid understanding of ML algorithms, evaluation techniques and feature engineering.
• Experience addressing production ML challenges (drift, data quality, leakage).
• Hands-on with distributed computing and large-scale data processing.
• Experience with ML lifecycle management platforms (MLflow).
• CI/CD pipelines design and maintenance (GitHub Actions).
• Strong SQL skills and working with large datasets.
• Able to deliver explainable AI methods (SHAP, attribution).
• Ability to mentor colleagues and drive engineering best practices.

Responsibilities

• Design, develop, deploy and maintain ML models throughout their lifecycle, including training, validation, production deployment, monitoring and retraining.
• Lead the development and implementation of applied AI solutions for customer value, churn, fraud detection and abuse prevention.
• Establish and optimise MLOps frameworks, including automated deployment pipelines, CI/CD processes and model lifecycle management.
• Develop monitoring systems to track model performance, data drift, data quality and business outcomes.
• Define and implement model retraining strategies and governance practices.
• Apply model explainability techniques to improve transparency and interpretability.
• Collaborate with Data Engineering to build scalable data pipelines and reliable infrastructure.
• Translate business challenges into scalable AI solutions with stakeholders.

Skills

Python

Software engineering

Machine learning

CI/CD

SQL

Spark / PySpark

MLflow

GitHub Actions

Model explainability (SHAP)

MLOps

Communication

Leadership

Tools

Spark / PySpark

MLflow

GitHub Actions

Job description

Salve.Inno Consulting is seeking a Senior Machine Learning Engineer to own end-to-end production AI solutions, from design to deployment and monitoring, with a focus on reliability and business impact. You will lead ML lifecycle, MLflow, CI/CD pipelines and MLOps practices, collaborating with Data Engineering, Product, Risk and Commercial teams to deliver scalable, explainable models and measurable value.

The role requires 5–8+ years of experience, advanced Python, Spark, MLflow and strong