What are the responsibilities and job description for the GenAI Architect position at Droisys?
Gen AI Architect
Location – Raritan, NJ (hybrid)
Qualifications:
Bachelor/Master degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field with 15 years of experience
2 years of experience in developing and implementing Generative AI models, with a strong understanding of techniques such as GPT, T5 and BERT
Project management and governance experience preferred. Candidates with Technical and management skills given stronger preference.
Life sciences experience preferred.
Experience with handling customers at SLT and VP level.
Proficiency in Python and have 8 years of experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras
Strong knowledge of data structures, algorithms, and software engineering principles
Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure
8 years of experience with advanced natural language processing ( NLP ) techniques and tools, such as SpaCy, NLTK, or Hugging Face
Familiarity with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly
Significant experience architecting cutting-edge MLOps systems in enterprise environments
Knowledge of software development methodologies, such as Agile or Scrum
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
Proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment. Able to execute thought leadership.
Responsibilities:
Design, develop, and implement Generative AI models and algorithms, using techniques such as GPT, T5, BERT
Collaborate with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals
Conduct research to stay up-to-date with the latest advancements in Generative AI , machine learning, and deep learning techniques, and identify opportunities to integrate them into customer products and services
Optimize Generative AI models for improved performance, scalability, and efficiency
Develop and maintain AI pipelines, including data preprocessing, feature extraction, model training, and evaluation
Contribute to the establishment of best practices and standards for Generative AI development within the organization
