Requirements:

8+ years of relevant MLE experience in natural language processing, deep learning, and AI model development.
Strong background in Python programming and deep learning frameworks like TensorFlow, PyTorch, or Hugging Face Transformers.
Expertise in parallel computing, distributed training frameworks (e.g., Ray Training, PyTorch Distributed), and efficient utilization of hardware resources.
Proficiency in data preprocessing, tokenization, embeddings, and language modeling techniques.
Passion for developing scalable, well-designed, and responsible AI solutions that positively impact society.
Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams.
Entrepreneurial spirit, self-motivation, and a bias towards action in fast-paced environments.

What You'll Be Doing:

Design, develop, and optimize large language models for various natural language processing tasks.
Implement and maintain training pipelines, leveraging distributed training and optimizing for performance and efficiency.
Collaborate with cross-functional teams to gather requirements, define model architectures, and iterate on model development.
Conduct model evaluations, performance analysis, and optimization to improve model accuracy and reduce biases.
Stay up-to-date with the latest research and advancements in the field of natural language processing, multimodal signals, and large language models.
Contribute to the development of best practices, guidelines, and ethical AI principles for responsible LLM development and deployment.