Experience working with recommendation engines, data pipelines, or distributed machine learning.
Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is highly desirable.
7 years of experience in research with sequential modeling or generative AI, deep learning architectures, and Transformers, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
5 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
Programming experience in C/C++, Java, Python, computer vision, self-supervised learning, transfer learning, and reinforcement learning.
Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras
Experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.
Strong knowledge of data structures, algorithms, and software engineering principles.
Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure.
Excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions.
Strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.
Possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment
Responsibilities
Utilize Large Language Models (LLMs), Open Source, Machine Learning, and numerical programming frameworks, to build transformative solutions
Understanding of AI Models, Large Language Models, and AI specialized infrastructure especially as it relates to AI trends and issues within businesses
Work with Product Development as a Generative Artificial Intelligence (AI) subject matter expert and architect and develop scalable, resilient, ethical AI solutions
Build solutions that align with responsible AI practices.
Architect and develop software or infrastructure for scalable, distributed systems and with machine learning technologies.
Work with both open source models(Tensorflow, PyTorch, Hugging Face Transformers) cloud solutions, internal solutions and external partners to deliver the best solutions
Optimize existing generative AI models for improved performance, scalability, and efficiency.
Develop and maintain AI pipelines, including data preprocessing, feature extraction, model training, and evaluation.
Develop clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.
Contribute to the establishment of best practices and standards for generative AI development within the organization.
