Software Engineer - Genetec AI Platform
HybridKraków, Lesser Poland, Poland
Job Summary
Build and maintain self-service data acquisition, annotation, and versioning capabilities to enable continuous movement from raw data to clean datasets. Facilitate experimentation by providing compute clusters for model training pipelines and ensuring full traceability of data, code, and artifacts across runs. Design and operate secure, automated deployment workflows that move models from experimentation to production, implementing continuous deployment pipelines with versioning and parallel deployments. Optimize runtime environments to meet latency and performance targets while supporting multi-cluster and multi-tenant scaling. Join a diverse team across Canada, France, and Poland to shape AI-driven innovation.
Required Qualifications
- Hands-on experience with MLFlow, KServe, AirFlow
- Knowledge on labelling/annotation tooling
- Experience with experiment tracking tools
- Familiarity with model runtimes and deployment (Triton Inference Server, OpenVino Model Server)
- Knowledge of DevOps, CI/CD for ML, GitOps workflows, and automated deployment strategies
- Proficiency in telemetry and data drift and quality monitoring
- Strong skills in Kubernetes and Terraform for infrastructure automation
- Experience with scaling services in cloud environments
- Solid coding skills in at least one language, Golang or .NET, and the motivation to learn Golang or .NET
Desired Qualifications
- Expertise in data platforms, including batch and streaming pipelines, ideally with knowledge of Databricks, Spark, and/or Delta Lake
- Knowledge in labelling/annotation tools
- Knowledge in experiment tracking tools
- Strong understanding of data quality, data versioning, and lineage tracking
- Knowledge of the Champion/Contender deployment model
- Understanding of responsible AI governance and compliance
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