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About the Role
IPRally is building AI-powered tools for understanding patents and technical knowledge. This role is crucial for ensuring the quality and delivery of patent data, which is the foundation of our product. You will work closely with a team of three data engineers and other engineering teams to model, process, and deliver data that powers our AI tools.
Responsibilities
- Model data to reflect the relationships between patents, research papers, and companies.
- Build agent harnesses and evaluations to enable autonomous data problem-solving and quality assessment.
- Develop and manage data pipelines using Python, Dagster, and data quality checks.
- Collaborate with product teams to define data requirements and formats.
- Partner with the ML team on the integration of machine learning in data processing.
- Explore and evaluate new data sources, including direct feeds from patent offices.
- Troubleshoot data source issues and identify alternative sources when necessary.
Requirements
- Experience building and running production pipelines on large, noisy real-world data, or equivalent experience in statistics or ML.
- Ability to make decisions in ambiguous situations with imperfect tools.
- Proficiency in building statistical evaluations and measurable targets.
- Experience building agent harnesses for data processing systems.
- Curiosity about the real-world context of data and its representation in systems.
- Ability to define data requirements based on user needs and use cases.
- Experience working directly with data consumers to prioritize tasks.
Skills
- Python
- Dagster
- Data Modeling
- Data Pipelines
- Data Quality Checks
- Machine Learning
- Distributed Processing (e.g., Ray)
- Polars
- Postgres
- Vespa
- Kubernetes
- GCP
Location
- Helsinki (preferred)
- Europe (remote possible)
Work Type
- Full-time
Experience Level
- Mid-level
- Senior
Salary/Compensations
- €66,000–€84,000 per year (based on €5,500–7,000/month)
- Equity
About the Company
- IPRally is building a new generation of AI powered tools for understanding patents and technical knowledge.
- Our product relies heavily on processing patent data from various global sources in different formats, including scanned documents.
- We leverage AI agents in our development process, enabling data-driven solutions where previously difficult.
- Our data stack includes Python, Dagster, Ray, Polars, Postgres, Vespa, Kubernetes, and GCP.