Machine Learning Lead Analyst

Qualifications

• 5 – 8 years of experience in technology

• 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.

• 5 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.