We are looking for an AI Engineer to develop reusable NTT AI Assets to accelerate GenAI and AI Use Cases from Ideation to MVP. He/She will also explore the AI landscape to pilot new GenAI tools within our ecosystem to rapidly test business value based on requirements. As part of the AI innovation pod, he/she plays an important role to create an agile lab with IP, ownership and control of any such developments belonging to NTT.
Job Description
Integral role in an agile AI innovation pod responsible for designing, building, validating, and deploying end-to-end machine learning systems.
Work with large and complex datasets to develop domain-based AI or GenAI models/solutions to deliver business value.
Build reusable AI assets, pilot new tools in the ecosystem and actively seek opportunities to finetune solutions and drive innovation.
Drive AI governance and best practices for AI development, in deployment and operations.
Key Roles and Responsibilities
● Design, develop, and deploy reusable domain-based AI and Generative AI assets using cutting-edge techniques such as GPT, VAE, and GANs.
● Create secure, scalable, and efficient cloud-based AI solutions that adapts to changing business needs.
● Continuously optimise AI pipelines, including data preprocessing, feature extraction, model training and evaluation, to ensure the best performance.
● Collaborate with subject matter experts to define AI project requirements and objectives that align with overall business goals and drive innovation.
● Stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques, and identify opportunities to integrate them into our products and services.
● Optimise existing AI solutions for improved performance, scalability, and efficiency.
● Promote AI governance and best practices in the development, deployment, and operations of AI systems to ensure responsible and ethical use of AI.
Knowledge, Skills, and Attributes
● Application knowledge of, Generative AI and machine learning concepts and technologies.
● Proficiency in programming languages such as Python, Java, or C++.
● Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Huggingface), deep learning techniques, natural language processing, LLMs
● Strong understanding of cloud platforms (preferred Azure).
● Strong analytical and problem-solving abilities.
● Ability to make data-driven decisions and assess the business impact of AI projects.
Academic Qualifications and Certifications
● Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
● Relevant programming qualifications and/or cloud certifications
● Relevant Agile certification is preferable.
Required Experience
At least 2 years of experence in the following
● Demonstrable experience with one or more programming languages (e.g. Python) and database languages (e.g. SQL)
● Demonstrable experience with data warehouse and data lake technical architectures, infrastructure components, ETL/ ELT, and reporting/analytic tools
● Experience with common AI and Generative AI technologies and libraries, such as NumPy, Matplotlib, Scikit, LangChain, Streamlit, LLM models
● Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc
● Demonstrable experience applying statistical methods and machine learning techniques to solve business problems
● Experience in working in micro-services architecture working with APIs development
● Demonstrable experience of full-stack software development with prolific coding abilities
● Experience with Agile Development Methodologies and Test-Driven Development
