Senior AI Engineer (WAT Remote)

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.

• 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:

• 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.

• 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.