• Established expertise and genuine passion for natural language processing (NLP), machine learning, deep learning, and large language models
• Minimum of 3 years in model training, deployment, and procedures for efficiently acquiring and validating human-labeled data
• Experience training, fine-tuning and deploying large language models (LLM)
• Proven track record of implementing NLP techniques to develop conversational agents, chatbots, or virtual assistants
• Proficiency with deep learning frameworks like TensorFlow, PyTorch, and JAX
• Familiarity with NLP toolkits such as spaCy and Hugging Face Transformers
• Solid communication skills complemented by a history of fruitful collaborations
• Strong foundation in algorithms, data structures, and object-oriented programming
• Self-motivated and adept at operating independently

Desirable

• Genies is hiring a Lead NLP Research Scientist to drive the development of our NLP technologies and products
• Seated in our San Mateo based headquarter and reporting to the VP of Engineering, this Lead NLP Engineer will play a pivotal role in utilizing advanced NLP and ML tools to create emotionally intelligent avatars that connect with users, and create a highly user centric content experience
• Your responsibilities include recognizing and responding to emotional cues, giving each avatar a distinct voice and persona, and tailoring data capture to the overall content experience
• You'll also be at the forefront of shaping the future of AI-driven content and gameplay, ensuring immersive and unique experiences
• You'll work hand in hand with our broader Avatar Tech and R&D team to integrate multimodal techniques, allowing avatars to understand and respond to text, motions, speech, gestures, and facial expressions
• Our mission is to revolutionize digital avatars and their ability to be interoperable across digital experiences; making them empathetic and authentic in user interactions, ushering in a new era of social engagement
• Identifying innovative NLP solutions for our product suite and defining the roadmap for their implementation
• Lead the training, fine-tuning, and deployment of large language models
• Oversee the AI lifecycle from data acquisition to model deployment and real-time monitoring, guaranteeing efficiency at each phase
• Collaborate with cross-functional units, fostering knowledge exchange and enhancing business impact through machine learning