The role involves designing MLOps platforms, implementing CI/CD pipelines, monitoring model performance, and collaborating with data scientists to productionize ML models. Mentorship to juniors is encouraged.
CAPCO POLAND
*We are looking for Poland based candidate. Hybrid work. Warsaw is preferred.
At Capco Poland, we’re not just another consultancy - we’re the spark behind digital transformation in the financial world. As a global leader in technology and management consulting, we thrive on helping clients tackle the toughest challenges across banking, payments, capital markets, wealth, and asset management.
Our secret?
A culture that’s fast, flexible, and fiercely entrepreneurial. We move quickly, think creatively, and always put our people first.
We’re passionate about growth - both for our clients and ourselves - and that means attracting the very best talent to join us on this exciting journey.
We’re proud to be:
• Trailblazers in banking, payments, capital markets, wealth, and asset management
• Champions of an agile, nimble, and innovative work environment
• Dedicated to building a team of top-notch professionals who share our drive and vision
• Trailblazers in banking, payments, capital markets, wealth, and asset management
• Champions of an agile, nimble, and innovative work environment
• Dedicated to building a team of top-notch professionals who share our drive and vision
THINGS YOU WILL DO
Platform Engineering for ML
- Design, build, and improve MLOps platform components that support the full model lifecycle (development à validation à deployment à monitoring).
- Create reusable templates and standardized pipelines to reduce time-to-production and improve consistency across teams.
Model deployment & release engineering
- Implement robust deployment patterns for credit risk models (primarily batch; other patterns as required).
- Build & maintain CI/CD pipelines using Jenkins and GitHub, with appropriate quality gates and traceability.
- Automate environment configuration and repeatability using Ansible.
Monitoring, observability & operational readiness
- Implement model and pipeline monitoring covering operational health, data quality signals, and model performance/drift indicators.
- Establish dashboards, alerting, and runbooks; partner with stakeholders to ensure alerts are actionable and aligned to business impact.
- Drive continuous improvement through post-release reviews and reliability enhancements (no on-call requirement).
Collaboration & stakeholder management
- Work closely with credit risk modellers to productionise models built with tools such as TensorFlow, MLFlow, and similar.
- Translate modelling needs into scalable engineering solutions, balancing pace with control expectations.
- Mentor junior team members (nice-to-have) and contribute to shared engineering standards and documentation.
SKILLS & EXPERIENCES YOU NEED TO GET THE JOB DONE
- 5+ years’ experience across MLOps/DevOps/Platform Engineering, with a track record of delivering production-grade ML or data solutions.
- Strong experience building CI/CD and automation using Jenkins and GitHub.
- Strong experience with Airflow (Bash), Bash itself, and Groovy for pipeline automation.
- Hands-on configuration automation using Ansible.
- Strong coding/scripting capability in Python (including PySpark), plus working knowledge of Spark.
- Experience with ML tooling such as MLFlow, TensorFlow, and similar, including model packaging and deployment considerations.
- Proven ability to implement observability (metrics/logs/dashboards/alerting), with tooling flexibility (e.g., Grafana, Splunk, or similar).
- Comfortable working in hybrid environments; experience with Hadoop and an ability to integrate with cloud services (preference for GCP).
Nice to have:
- Exposure to GCP services, especially Vertex AI and BigQuery.
- Experience with secrets management (tooling flexible).
- Familiarity with Model Risk Management, SDLC controls, and data lineage concepts in regulated environments.
- Prior experience mentoring junior engineers and helping teams adopt standard patterns.
ONLINE RECRUITMENT PROCESS STEPS
- Screening call with the Recruiter
- Capco Hiring Manager Interview
- Client’s interview
- Feedback/Offer
We offer a flexible collaboration model based on a B2B contract, with the opportunity to work on diverse projects.
Top Skills
Airflow
Ansible
Bash
BigQuery
DevOps
GCP
Git
Grafana
Groovy
Hadoop
Jenkins
Mlflow
Mlops
Platform Engineering
Pyspark
Python
Spark
Splunk
TensorFlow
Vertex Ai
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