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Awarri

Senior AI Engineer (WAT Remote)

Reposted 22 Days Ago
In-Office or Remote
8 Locations
Mid level
In-Office or Remote
8 Locations
Mid level
The Senior AI Engineer will design, develop, and deploy language models for AI, focusing on African languages, collaborating with experts, and ensuring contextual relevance.
The summary above was generated by AI

At Awarri, our mission is to enable the development and adoption of frontier technology on the African continent, starting in Nigeria, by building lasting technology solutions and creating a brighter future using the power of AI.

We are achieving that mission through the development of Language Models designed to represent and empower African languages and contexts. Join our team of AI innovators as we shape the future of natural language processing (NLP) in Africa, focusing on cultural preservation, linguistic diversity, and cutting-edge generative AI solutions.

Why Join Awarri?

  • Be part of a pioneering initiative to shape the future of AI in Africa.
  • Collaborate with a passionate and diverse team of engineers, researchers, and innovators.
  • Contribute to projects with real-world impact, driving inclusivity and representation in AI.


Senior AI/ML Engineer

The Senior AI/ML Engineer will play a central role in the design, development, and deployment of language models tailored to low-resource languages and diverse cultural contexts. They will collaborate with interdisciplinary teams to advance Awarri's mission of creating contextually aware and impactful AI solutions.

Responsible for

  • Lead the design, training, and optimization of large-scale language models for African languages and dialects, ensuring accuracy and contextual relevance.
  • Develop innovative solutions for data pre-processing, tokenization, and embedding, specifically for low-resource and multilingual datasets.
  • Implement and fine-tune transformer-based architectures (e.g., GPT, BERT) for specific NLP applications like text generation, translation, and sentiment analysis.
  • Design scalable pipelines for data collection, annotation, and pre-processing to support model development.
  • Collaborate with linguists, cultural experts, and AI researchers to ensure the LLM aligns with diverse user needs and cultural sensitivities.
  • Deploy, monitor, and maintain production-level LLM systems in cloud-based environments, ensuring robust performance and reliability.
  • Establish frameworks for model evaluation, leveraging metrics such as perplexity, BLEU, and human-centered benchmarks.
  • Stay at the forefront of advancements in NLP, LLMs, and generative AI, integrating emerging research into Awarri's language model development efforts.
  • Document processes, architectures, and outcomes for knowledge sharing and collaboration across teams.
  • Technical Proficiency:

Requirements

  • Minimum of 3 years in AI/ML engineering, with a focus on NLP and large language models.
    • Strong expertise in transformer-based models such as GPT, BERT, T5, or equivalent.
    • Proficiency with frameworks like TensorFlow, PyTorch, or Hugging Face Transformers.
    • Experience in training and fine-tuning LLMs on large-scale, multilingual datasets.
    • Strong programming skills, with expertise in NLP libraries and tools.
  • Data and Cloud Expertise:
    • Experience in building pipelines for text data collection, pre-processing, and annotation.
    • Familiarity with cloud platforms like AWS, Azure, or GCP for deploying scalable NLP solutions.
  • Innovation & Collaboration: Demonstrated ability to work on open-ended research problems and collaborate with interdisciplinary teams, including linguists and cultural experts.
  • Impact: A proven track record of developing and deploying NLP systems that deliver measurable value in production.

Preferred Skills

  • Experience working with low-resource languages or multilingual NLP.
  • Knowledge of cultural and linguistic nuances in African contexts.
  • Familiarity with ethical AI principles, particularly for language technologies.

Top Skills

AWS
Azure
GCP
Hugging Face Transformers
PyTorch
TensorFlow

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