NTT DATA North America
Python Gen AI Developer
Job Description
NTT DATA's Client is currently seeking a Python Gen AI Developer to join their team in Irving, Texas (US-TX), United States (US).
Day to Day job Duties:
Design, implement, and optimize generative AI models using frameworks like TensorFlow, PyTorch, or JAX. This includes working with architecture like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Large Language Models (LLMs)
Research and implement machine learning algorithms and tools
Integrate generative AI models into production systems and applications, often involving APIs, microservices, and cloud platforms (AWS, Azure, GCP).
Manage and direct research and development processes to meet the needs of our AI strategy
Develop machine learning applications in alignment with project requirements and business goals
Perform machine learning tests and statistical analysis to fine-tune the machine learning systems
Select appropriate datasets and data representation methods
Extend existing machine learning libraries and frameworks
Train systems and retrain as necessary
Work with the engineering and leadership teams on the functional design, process design, prototyping, testing, and training of AI/ML solutions
Skills required: Overall 7+ years of experience.
3+ Years of strong Python coding skills and python libraries (like NumPy, Pandas etc.)
2+ Years of solid understanding of generative AI models (GANs, VAEs, LLMs) and their underlying principles
2+ Years of experience on any of the Python web development frameworks (FastAPI, Flask, Django)
Strong experience in using Neo4J, Mongo DB
Experience in working as part of scrum team with knowledge of related ceremonies.
Strong communication skills.
Understanding and experience on Gen AI implementations
Experience on Langchain, Vector DB, Embeddings or related frameworks
Experience on AI/ML model implementations using scikit learn, Tensor flow etc.,
Experience with Chat, IVR, Banking will be plus
Google Cloud (GCP) knowledge
NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
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Research and implement machine learning algorithms and tools
Integrate generative AI models into production systems and applications, often involving APIs, microservices, and cloud platforms (AWS, Azure, GCP).
Manage and direct research and development processes to meet the needs of our AI strategy
Develop machine learning applications in alignment with project requirements and business goals
Perform machine learning tests and statistical analysis to fine-tune the machine learning systems
Select appropriate datasets and data representation methods
Extend existing machine learning libraries and frameworks
Train systems and retrain as necessary
Work with the engineering and leadership teams on the functional design, process design, prototyping, testing, and training of AI/ML solutions
Skills required: Overall 7+ years of experience.
3+ Years of strong Python coding skills and python libraries (like NumPy, Pandas etc.)
2+ Years of solid understanding of generative AI models (GANs, VAEs, LLMs) and their underlying principles
2+ Years of experience on any of the Python web development frameworks (FastAPI, Flask, Django)
Strong experience in using Neo4J, Mongo DB
Experience in working as part of scrum team with knowledge of related ceremonies.
Strong communication skills.
Understanding and experience on Gen AI implementations
Experience on Langchain, Vector DB, Embeddings or related frameworks
Experience on AI/ML model implementations using scikit learn, Tensor flow etc.,
Experience with Chat, IVR, Banking will be plus
Google Cloud (GCP) knowledge
NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
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