Machine Learning Infrastructure Engineer
New
Wrocław, Fabryczna 6, Wrocław, Country code: plFull-TimeSenior
Salary23,000 - 25,000 PLN per month
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonGCPKubernetesMachine LearningNumpyPyTorchSnowflakePandasBigQueryMLOps
Requirements
- 5+ years of professional experience in Machine Learning Engineering, Data Engineering, or ML Infrastructure roles
- Strong proficiency in Python and its scientific ecosystem (NumPy, Pandas, PyTorch)
- Proven experience building and operating production-grade ML systems in cloud environments
- Solid understanding of MLOps practices, including model registries, feature stores, CI/CD for ML, and deployment patterns
- Hands-on experience with workflow orchestration tools such as Argo Workflows or Prefect
- Strong experience with cloud data warehouses (BigQuery or Snowflake), including performance tuning and complex SQL optimization
- Experience working in cloud-native environments (preferably GCP) and Kubernetes-based infrastructure
- Familiarity with AI-assisted development workflows / coding agents used in production environments
- Ability to communicate effectively with both engineering teams and scientific/research stakeholders
Responsibilities
- Build and scale infrastructure for deploying ML models (e.g. GNNs, Transformers) in chemistry and structural biology domains
- Productionize research-grade models into robust, scalable, and maintainable systems
- Design and maintain cloud-native data architectures (BigQuery / Snowflake) for large-scale molecular datasets
- Develop and orchestrate ML pipelines using tools such as Argo Workflows or Prefect
- Implement and optimize distributed training and inference workflows using Ray / Anyscale
- Contribute to development and deployment of predictive models within a computational drug discovery platform
- Design and maintain LLM-based agentic systems supporting automated drug design workflows
- Collaborate closely with ML infrastructure and research teams to ensure alignment between scientific needs and engineering standards
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