Machine Learning Engineer
vor 4 Wochen
We are seeking an experienced Machine Learning Engineer to join our team at one GmbH. As a key member of our engineering team, you will play a vital role in developing our novel Packaging Development AI Engine.
As an expert in Applied AI, you will use your skills to develop and integrate new AI and ML approaches to power our internal Material Science Platform. This role requires a strong scientific background or experience with scientific data, as you will be developing machine learning and LLM systems based on materials engineering, chemistry, and physics-derived knowledge.
You will also be designing AI agents that emulate scientific reasoning. Domain expertise is essential for accurately developing, interpreting, and managing these systems. In a startup environment, you will need to work independently, applying advanced ML techniques to complex, scientifically-sourced data to ensure robust performance.
This role reports to Marta Rodriguez, Head of Software and Data, and has key stakeholders in other data and software engineers, as well as team members throughout the company.
Given the remote-first nature of our team, this role can be based anywhere but willing to work approx UTC/UTC+2 core hours, in order to overlap with the bulk of our European-based team.
Key Responsibilities- Develop our core AI Engine
- Coordinate ML requirements with stakeholders
- Be our ML champion
You will be responsible for developing and implementing advanced machine learning or AI systems, experience with Deep Learning or LLMs is preferred. You will also be working closely with stakeholders and other engineers to evaluate and optimize our systems for performance and accuracy.
Requirements- Extensive hands-on experience of developing and implementing advanced machine learning or AI systems
- Experience spearheading ML and data-heavy projects
- Experience bringing machine learning applications to production (end-to-end development)
- Strong programming skills in Python, familiarity with libraries and tools such as langchain/haystack, pytorch/tensorflow, spancy/nltk, scikit-learn, MLflow, GCP, VertexAI, etc.
- Experience with vector databases and knowledge graph systems is a plus
- Experience working with complex, scientific/chemistry-like data and metadata, such as lab-generated measurements and experimental conditions, industrial trial data, etc.
- Strong problem-solving skills and ability to work independently in a remote setup
- Ability to work independently and proven stakeholder management
- Experience implementing and coordinating with domain experts in multifunctional environments
- Fluency in English, as this is our working language
Protecting our planet by developing materials for clean & closed material loops.
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