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
Capco Edinburgh, Scotland Office
The Eagle Building, 19 Rose St., Edinburgh, United Kingdom, EH2 2PR
Similar Jobs at Capco
Fintech • Professional Services • Consulting • Energy • Financial Services • Cybersecurity • Generative AI
The Data Engineer will design and maintain data pipelines and architectures, ensuring reliable data for decision-making through collaboration with data analysts and scientists.
Top Skills:
AirflowAWSAzureDbtDockerGCPHadoopInformaticaKubernetesPower BIPythonScalaSparkSQLTableauTalend
Fintech • Professional Services • Consulting • Energy • Financial Services • Cybersecurity • Generative AI
The Machine Learning Engineer will design, build, and deploy scalable ML solutions, collaborating with teams to operationalize models and ensure their performance and reliability.
Top Skills:
AirflowAWSAzureDockerGCPKubeflowKubernetesMlflowPandasPythonPyTorchScikit-LearnSparkTensorFlow
Fintech • Professional Services • Consulting • Energy • Financial Services • Cybersecurity • Generative AI
Lead end-to-end product strategy and delivery for Commercial & Specialty Insurance, translating market processes into user stories, defining success metrics, and collaborating with data and engineering teams to deliver data models, APIs, and integrated digital platforms while managing cross-functional stakeholders.
Top Skills:
Agentic AiAPIsGenaiPplWhitespace
What you need to know about the Edinburgh Tech Scene
From traditional pubs and centuries-old universities to sleek shopping malls and glass-paneled office buildings, Edinburgh's architecture reflects its unique blend of history and modernity. But the fusion of past and future isn't just visible in its buildings; it's also shaping the city's economy. Named the United Kingdom's leading technology ecosystem outside of London, Edinburgh plays host to major global companies like Apple and Adobe, as well as a growing number of innovative startups in fields like cybersecurity, finance and healthcare.
