The Role
At the GenAI Pod, we’re pushing the boundaries of what’s possible. As a Senior Associate in our GenAI Lab start-up, you will:
Pioneer the design, development, and deployment of production machine learning pipelines
Shape machine learning-enabled, Audit applications
Deliver high-quality code contributions to our evolving codebase
Monitor and review live production models
Lead and guide workstreams on projects within your specialisation
Mentor and manage junior engineers on impactful workstreams
Skills and Experience
A passionate data scientist, who has invested time in understanding Generative AI and experienced the power of LLM
Practical experience from industry and professional services in delivering significant and valuable advanced analytics projects and/or assets
Engagement of technical and senior stakeholders
Ability to manage and coach a team of data scientists
Delivery of projects on time and in budget for high profile clients
Understanding of requirements for software engineering and data governance in data science
We make extensive use of the following technologies in our team. We expect you to be fluent with using these tools and practices on a daily basis.
Bachelor's degree (or more) in computer science / Data Science or a related technical discipline
Experience in Natural Language Processing
Extensive experience with modern Deep Learning (PyTorch/TensorFlow)
Experience with any of the following NLP tasks - named entity recognition, intelligent document processing, website parsing & classification, sentiment analysis, information retrieval, entity matching & linking, spelling correction
Strong knowledge of Mathematical Statistics, Algorithms & Data Structures, ML Theory
Strong knowledge of Python & SQL
Strong debugging skills
Git for version control
Azure / GCP for our cloud backend
Skills we’d like to hear about
Experience working with large data pipelines (using technologies such as Beam or Kafka)
Experience in LLMs using OpenAI, Gemini or open source models
Exposure to other programming languages (such as Java)
Experience of working on a project using agile concepts (such as working in sprints)
Familiarity with working in an MLOps environment.
Experience working with search engines (such as Elasticsearch)
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