We are on a mission to reinvent the way information is structured and served online, to make it easier than it ever has been for individuals to search, discover and learn.
Who we are and what we do
We believe that the current paradigm of search (Google) is quite terrible and outdated - namely:
- It doesn't answer your questions, rather, it points you to a list which you have to select from, and that list...
- Surfaces resources that are rarely useful (SEO'd to hell)
We are constructing searchable, contextualized knowledge graphs using NLP and proprietary algorithms. We will transform information silos in different verticals to make the search, discovery and learning of relevant information faster and simpler than it ever has been.
We are backed by the most incredible investors in the Valley, including Josh Buckley and Village Global.
Who do we need?
Atomic Search is looking for a data engineering supergenius to join our founding team - someone who:
- Is driven by our mission to significantly enhance human thinking and democratize education
- Has 4 years of professional data engineering experience - optional
- Is excited about operating in uncharted territory, working daily with cutting edge technology and implementations. This role will involve constant learning, iteration and revision.
- Is excited about developing a truly innovative product in a completely greenfield space
- Wants to be a part of a small, fast moving, mission-driven, well-capitalized team where they have ownership in the long term success of the company
- Fluency in Python for Data Science
- Fluency in at least one statically-typed language (Java, Go, C++ etc)
- Proven experience within at least one Machine-Learning framework (PyTorch, TensorFlow etc.)
- Familiarity with at least one enterprise-grade Natural Language Processing framework (spaCy, Spark NLP, nltk etc)
- Familiarity with popular graph database solutions (Neo4j, ArangoDB etc.)
- Knowledge of popular graph database schemas (RDF/OWL, Labelled Property Graphs, Entity/Relation etc.)
- Experience with web-scraping applications
- Familiarity with Graph Machine Learning approaches and use cases
- Experience training custom machine-learning models for NLP tasks
- Experience with complexity and optimisation modelling (Big O notation )
- A familiarity with Object-Role Modelling for knowledge graphs
- Proficiency in low-level languages like Assembly, C or even Cython
- A working knowledge of knowledge graphs, and a familiarity with applied Discrete Mathematics more generally
- A strong background in Statistics
- A strong understanding of advanced set theory and notation
- A familiarity with chaotic systems
What will you be doing?
This team member will help architect and implement an end-to-end unstructured text to knowledge graph solution. They will take the lead on designing cutting-edge NLP systems, implementing clever heuristics and custom machine-learning techniques to extract accurate data from unstructured text. They will add contextual density to our knowledge graph by researching and implementing state of the art Graph Machine Learning techniques.
Your (tentative) day to day:
- Daily stand-ups with Atomic's team
- Create pipelines for processing unstructured text
- Join engineering team as lead data engineer in sprints to MVP
- Stay up-to-date with the latest research in NLP, semantic processing and knowledge graph generation