Machine Learning Engineer driving materials discovery and AI adoption in chemistry. Enhancing ML/AI infrastructure and deploying models for production environments.
Responsibilities
Drive materials discovery and development into a new era.
Accelerate the adoption of AI in chemistry and materials science.
Shape and enhance our ML/AI infrastructure with strong support from our platform development team.
Co-develop both existing and new ML/AI models, actively contributing to the end-to-end lifecycle from design through deployment.
Oversee data management operations in close collaboration with our platform team to ensure data quality and accessibility.
Regularly deploy code to production through our CI/CD pipeline, ensuring reliability and robustness in a live environment.
Requirements
Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Data Science, or similar)
Demonstrated experience in building and/or maintaining ML/AI platforms
Proven track record of deploying ML models in production environments, including dataset preparation and automation
Minimum of 3 years’ experience working with cloud providers (AWS)
At least 4 years of experience with Python or similar programming languages, with extensive experience in production environments
Solid understanding of container orchestration tools like Kubernetes
Hands-on experience in frameworks such as Kubeflow, MLflow, and/or Apache Spark
Strong communication skills with a collaborative approach to working in an interdisciplinary team
Experience or keen interest in data platform engineering is a plus.
Benefits
Flexible working hours and home office days.
30 days of vacation per year.
Personal development budget of 1,000 EUR per year.
Top-notch coffee at our favorite coffee shop next door for only 1 EUR.
Free fruit and a large selection of drinks (including soda, juices, Mate).
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