Summary
✨ AI‑Generated
An ML platform engineering role focused on building and scaling production-grade MLOps infrastructure. You will standardize Databricks environments, CI/CD, and model monitoring while improving an AWS-based machine learning platform. The position combines Python automation, Terraform, cloud architecture, multi-tenant design, and close collaboration with data science and ML engineering teams.
Highlights
Build and scale a production-grade ML platform serving hundreds of data scientists and engineers. The role offers substantial ownership of Databricks MLOps, AWS SageMaker, infrastructure automation, model deployment, reliability, and security.
Description
About The Role
You will join a team responsible for building and scaling the ML platform used by 300+ data scientists and ML engineers across 60+ teams.
Your work will directly impact how machine learning models are deployed to production — reliably, securely, and at scale.
You’ll spend most of your time implementing and standardising Databricks MLOps (environments, CI/CD pipelines, model monitoring) while also contributing to the evolution of a battle‑tested AWS SageMaker platform.
You Day-to-day
Design, build, and scale a production-grade ML / MLOps platformImplement Databricks MLOps (environments, CI/CD pipelines, monitoring)Maintain and improve the AWS SageMaker ML platformAutomate infrastructure and workflows using Python and Infrastructure‑as‑Code (Terraform)Design solutions for a large-scale multi-tenant architecture (60+ teams, 3 AWS accounts)Partner closely with data scientists and ML engineers to enable production model deploymentsEnsure platform reliability, security, observability, and cost efficiency
Who We’re Looking For
Have 4–6 years of experience building production infrastructure for ML or data workloadsKnow Databricks or AWS SageMaker deeply (Databricks experience is strongly preferred)Are strong in AWS fundamentals (IAM, networking, compute - beyond console clicking)Can confidently write Python automation and Terraform / IaC without relying on basic syntax searchesUnderstand the full ML lifecycle: training, versioning, deployment, monitoringCan design and ship solutions independently, without constant hand‑holdingHave delivered non‑trivial CI/CD pipelines to productionExperience with workflow orchestration and CI/CD tools such as Apache Airflow and JenkinsHave hands‑on experience with Kubernetes (EKS)
Nice To Have
Apache AirflowOAuth / Amazon Cognito, API GatewayMonitoring tools such as Prometheus, Grafana, New RelicCloud cost optimisation experienceGitOps tooling (FluxCD, ArgoCD)
Come and join us!
For Poland: In this position you will earn no less that 17 600 PLN gross monthly
Relocation support is not available for this job
Please note that only on-line applications will be taken into consideration.
Only selected candidates will be contacted.
At PMI we run the business in line with ethical principles and encourage SpeakUp culture.
We care for equal chances and fair treatment.
If you find anything that violates these principles in this job offer or the recruitment process, you may contact our Ethics and Compliance Team at PMIEthicsandCompliance@pmi.com.
Read more about Ethics&Compliance at PMI – here.
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