Open Source AI Engineers (time series), multiple roles
*(M/W/D)
Open Source Focus: sktime & time series AI ecosystem
ecoSPECS and the German Center for Open Source AI (GC.OS) are partnering to build the the next generation of open, modular, and transparent AI tools for time series analysis and forecasting – embedded with the BioPharma Cluster South Germany, world-leading manufacturing champions, and energy companies.
As active contributors to the open-source community, we believe in advancing scientific and engineering excellence through collaboration, direct engagement with end users, and openness.
We are looking for multiple Open Source AI Engineers to help lead development and innovation around sktime – the open-source Python library for AI with time series – and the GC.OS software stack.
You’ll work at the intersection of software engineering, industry applications, and community development, helping shape the future of time series AI.
- Design, implement, and maintain features and extensions for the sktime.
- Work in a community of practice with multiple industry use case settings, to define deployment standards and APIs.
- Develop new features for forecasting, classification, or detection within sktime’s modular framework.
- Lead open-source engineering best practices — CI/CD, testing, documentation, and release management.
- Engage with the open-source community: review PRs, mentor contributors, and guide design discussions.
- Drive integration and interoperability with adjacent ecosystems (e.g., scikit-learn, PyTorch, Hugging Face).
- Support internal and partner teams adopting sktime in production pipelines.
Required Skills & Experience:
- experience in AI/ML engineering or applied AI development, 5+ years for senior role, 2+ years for junior role
- Proven track record contributing to or maintaining Python libraries (preferably open-source).
- Strong software engineering background: Python, NumPy, pandas, scikit-learn, PyTorch, pytest, and git/GitHub workflows.
- Experience with time series analysis, forecasting, or signal processing.
- (for Senior:) Familiarity with API design, modular architectures, and performance optimization in Python.
- Excellent communication and collaboration skills, (for Senior:) track record in leading community discussions or code reviews.
Nice to Have:
- Contributions to sktime, related libraries (scikit-learn, PyTorch, statsmodels, PyTorch Forecasting, etc.), or the GC.OS software stack.
- Knowledge of MLOps tools (MLflow, DVC, Airflow) or deployment frameworks.
- Experience building interactive dashboards or front-end interfaces for data visualization (e.g., Streamlit, Dash, Plotly, or React-based tools).
- Familiarity with pharma, life sciences, or energy sector use cases, such as demand forecasting, predictive maintenance, or clinical time series analysis.
- Background in research software engineering or scientific computing.
- Experience in mentoring contributors or leading open-source governance processes.
TOGETHER
WE ARE
AWESOME.
Was wir bieten
- Work at the heart of the open-source time series ML ecosystem.
- Collaborate with world-class contributors, industry teams, and research groups.
- Shape the technical direction of one of the most widely used time series libraries.
- Competitive compensation, flexible remote work, and conference travel support.
- Be part of a mission to make open, transparent, and democratically governed AI tooling the global standard.
TOGETHER
WE ARE
AWESOME.
Open Source Focus: sktime & time series AI ecosystem
ecoSPECS and the German Center for Open Source AI (GC.OS) are partnering to build the the next generation of open, modular, and transparent AI tools for time series analysis and forecasting – embedded with the BioPharma Cluster South Germany, world-leading manufacturing champions, and energy companies.
As active contributors to the open-source community, we believe in advancing scientific and engineering excellence through collaboration, direct engagement with end users, and openness.
We are looking for multiple Open Source AI Engineers to help lead development and innovation around sktime – the open-source Python library for AI with time series – and the GC.OS software stack.
You’ll work at the intersection of software engineering, industry applications, and community development, helping shape the future of time series AI.
- Design, implement, and maintain features and extensions for the sktime.
- Work in a community of practice with multiple industry use case settings, to define deployment standards and APIs.
- Develop new features for forecasting, classification, or detection within sktime’s modular framework.
- Lead open-source engineering best practices — CI/CD, testing, documentation, and release management.
- Engage with the open-source community: review PRs, mentor contributors, and guide design discussions.
- Drive integration and interoperability with adjacent ecosystems (e.g., scikit-learn, PyTorch, Hugging Face).
- Support internal and partner teams adopting sktime in production pipelines.
Required Skills & Experience:
- experience in AI/ML engineering or applied AI development, 5+ years for senior role, 2+ years for junior role
- Proven track record contributing to or maintaining Python libraries (preferably open-source).
- Strong software engineering background: Python, NumPy, pandas, scikit-learn, PyTorch, pytest, and git/GitHub workflows.
- Experience with time series analysis, forecasting, or signal processing.
- (for Senior:) Familiarity with API design, modular architectures, and performance optimization in Python.
- Excellent communication and collaboration skills, (for Senior:) track record in leading community discussions or code reviews.
Nice to Have:
- Contributions to sktime, related libraries (scikit-learn, PyTorch, statsmodels, PyTorch Forecasting, etc.), or the GC.OS software stack.
- Knowledge of MLOps tools (MLflow, DVC, Airflow) or deployment frameworks.
- Experience building interactive dashboards or front-end interfaces for data visualization (e.g., Streamlit, Dash, Plotly, or React-based tools).
- Familiarity with pharma, life sciences, or energy sector use cases, such as demand forecasting, predictive maintenance, or clinical time series analysis.
- Background in research software engineering or scientific computing.
- Experience in mentoring contributors or leading open-source governance processes.
Was wir bieten
- Work at the heart of the open-source time series ML ecosystem.
- Collaborate with world-class contributors, industry teams, and research groups.
- Shape the technical direction of one of the most widely used time series libraries.
- Competitive compensation, flexible remote work, and conference travel support.
- Be part of a mission to make open, transparent, and democratically governed AI tooling the global standard.