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Responsibilities:
- Analyze and enhance biological knowledge graphs.
- Develop strategies to enrich data in knowledge graphs.
- Build ML models for classification and clustering.
- Deliver scalable, production-ready ML solutions.
- Collaborate with product, science, and engineering teams.
Requirements:
- 5+ years as an ML engineer in industry.
- Proficiency in Python and PyTorch.
- Expertise in NLP, RAG, and LLM techniques.
- Experience with graph machine learning.
- Degree in Software Engineering or related field.
Benefits:
- Cutting-edge work in ML and graph ML.
- Collaborative, growth-focused environment.
- Engagement with the ML/AI community.
