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Role requirements:
Starmind connects you to the people who know the solution to your problem. At our core is our knowledge engine which models how people in an organisation interact with the various areas of knowledge and how these areas relate to one-another.
We are looking for an AI/ML Engineer to join our team and help improve our automatic knowledge graph generation that is the foundation for this knowledge engine. Here are some of the things that you could do. You would not be expected to do all of these, and new tasks may arise as well
- Design, refine and implement model architectures for classification and retrieval
- Gather and generate large volumes of training data for model training
- Create and manage generative AI pipelines for enriching knowledge graphs
- Setup and maintain ML infrastructure
- Integrate ML functionality and work-flows into our product's back end
- Implement feedback mechanisms to turn user interactions into feedback for our models
- Improve retrieval and querying of data for better performance of our ML-based functionality
- Support our backend team with more traditional functionality such as search.
Core requirements:
- Experience working in a Software engineering environment, i.e. version control, and project management (git, JIRA)
- We welcome applications from promising graduate candidates if they have strong experience in other requirements.
- Experience with Python and a Machine Learning framework (ideally pytorch)
- Experience with one modern statically typed programming language (e.g. Scala, Kotlin, Java, Rust, C++, Swift, Go, Typescript). Our backend is written in Scala, and experience with strongly typed languages is a requirement to get you onboarded.
- Experience working with LLMs either via API or locally
- Proactive (bias for action), but quick to reach out for help / brainstorming / rubber-ducking
- Collaborative / not-territorial
- Willingness to learn
- Natural Language Processing
- Huggingface transformers
- SQL
- Data cleanup and training data generation
- Backend web development
- Exploratory ML experimentation and data analysis
- Elasticsearch
- Kubernetes
- ML Inference runtimes
- Apache Spark
- AI Coding tools
- Communication
- Documentation
- Quality assurance mindset
Key Skills
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