Natural Language Processing (NLP) Engineers - Senior
Role Description And Responsibilities
Pangaea is looking for a talented engineer to join its founding technical team to lead the productization of cutting-edge NLP algorithms in Pangaea’s core product (Pangaea’s Intelligence Extraction and Summarisation – PIES). A strong software engineering background, knowledge and skills on Machine Learning especially Natural Language Processing are essential. This role is open to senior engineers.
Key Technical Responsibilities:
- Take the lead in product architecture and feature design, representing the needs of the user and other stakeholders.
- Design, maintain and implement product roadmap according to the requirements.
- Design and develop robust, flexible and efficient product architecture.
- Design and adopt cutting-edge NLP algorithms to address real-world challenges such as intelligence extraction and prediction.
- Productise, develop, optimise and deploy NLP algorithms, supportive modules (such as architects, data processors, APIs) and other features in Pangaea’s product PIES.
- Adopt approaches which maximise the value to the end user, while minimise technical complexity.
- Prioritise tasks in weekly or bi-weekly sprint planning sessions to make sure we are regularly delivering small improvements, rather than only focusing on big feature releases.
- Monitor the impact of new features and releases of products, to determine if they achieved the goals set out for them at the start.
- Identify suitable candidates to build the NLP product team.
- Publish origin research and engineering work to conferences and journals.
This role will also involve working with the internal teams to:
- Understand the users they engage with and the problems, pain points and requests they are seeing.
- Clearly communicate our roadmap and product changes in advance of their launch.
- Run early rounds of internal feedback gathering, before we launch to users.
- Understand how our internal tooling can be improved for internal users.
- Understand the high-level company vision and goals, and make sure these are reflected in ongoing product development.
As an NLP engineer, you will be involved in leadership, product decisions and coordination between teams that go into the above process.
Mandatory Requirements
Technical Skills:
- At least 3-year experience in building commercial software systems in machine learning and deep learning especially NLP.
- With university qualification (Bachelors, Masters, Doctorate) who have completed at least two years of university study in Computer Science, Informatics, Data Science, Engineering, or related.
- Experience (classroom/work) in Machine learning, Natural Language Processing, Algorithmic Foundations of Optimization, Data Science, Data Mining and/or Bioinformatics.
- Experience on general programming languages: Python, C++, Java, etc.
- Experience with deep learning, machine learning and NLP frameworks such as PyTorch (or TensorFlow), HuggingFace Transformer, Scikit-learn.
- Experience with working in Linux.
Personal Traits:
- A strong intuition for what makes products a joy to use.
- Empathy for how different users will need different things out of a product at different stages, and how to effectively serve these different needs in one product.
- Strong communication and mediation skills.
- Strong people skills and the ability to engage all levels of the organization (especially the front line).
- Ability to work collaboratively in a team environment.
- Ability to communicate complex ideas effectively, both verbally and in writing, in English.
- A strong software engineering background with machine learning expertise to understand how the user facing product will tie into backend and architectural decisions.
Nice to Have:
- Experience with cloud platforms such as AWS, Azure, Google Cloud Platform.
- Experience with research communities and/or efforts, including having published papers (being listed as author) at AI/ML/NLP/CV conferences (e.g. NeuraIPS, ICML, ICLR, ACL, EMNLP, NAACL, CVPR, KDD etc) and biomedical journals.