ET - Senior Group Technical Architect

ET - Senior Group Technical Architect

Job Description (Posting).

Job Title: Gen AI ArchitectJob Description: We are seeking a highly skilled Generative AI Architect to join our dynamic team and drive the development of advanced AI systems that have capabilities to learn, reason and make decisions autonomously.Key Responsibilities: AI Systems Architecture: Design and develop the architecture and infrastructure for Gen AI systems, including mechanisms for data storage, processing, and retrieval. Ensure the systems scalability, flexibility, and efficiency to handle large algorithms. Algorithm Development: Develop and implement advanced AI algorithms and models, including machine learning, deep learning, and neural networks. Continuously evaluate and improve these algorithms to enhance system performance and accuracy. Data Integration: Identify relevant data sources and design methods for data collection, integration, cleansing, and transformation. Collaborate with data scientists and engineers to ensure the quality and relevance of data for AI model training. Model Training and Evaluation: Train AI models using supervised, unsupervised, or reinforcement learning techniques. Implement evaluation methodologies to measure the performance and effectiveness of trained models. Fine-tune models based on feedback and data insights. Neural Network Design: Design and optimize deep learning neural networks for various AI tasks, such as natural language processing, computer vision, recommendation systems, and predictive analytics. Implement innovative architectures and techniques to improve model accuracy and efficiency. System Integration: Collaborate with software developers and engineers to integrate AI systems into existing platforms or applications. Ensure seamless communication and compatibility between AI components and other software modules. Ethical and Responsible AI: Adhere to ethical AI practices, such as fairness, transparency, and accountability. Address biases and potential risks associated with AI systems to ensure responsible deployment and usage. Research and Innovation: Stay updated with the latest advancements in AI technologies, frameworks, and algorithms. Conduct research and experimentation to explore innovative approaches and techniques that can enhance AI capabilities. Teamwork and Communication: Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to define AI requirements and deliver AI solutions that meet business objectives. Communicate complex AI concepts and solutions effectively to both technical and non-technical audiences. Mandatory Qualifications/Skills: A bachelors or masters degree or equivalent in computer science, Artificial Intelligence, or related field. Experience with large language models (LLMs) and prompt engineering. Experience in designing and developing AI systems, including machine learning, deep learning, and neural networks. Strong programming skills in languages such as Python, R, or Java Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or Keras. Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms. Solid understanding of AI concepts, algorithms, and methodologies. Knowledge of designing large scale AI solutions, data integration, cleansing, and transformation techniques. Excellent problem-solving and analytical skills, with the ability to think creatively and provide innovative solutions. Strong communication and collaboration skills to work effectively in multidisciplinary teams. Knowledge of ethical AI practices and laws is a plus. Preferred Skills : Knowledge of NVIDIA CUDA, cuDNN, TensorR

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ET - Senior Group Technical Architect

Job Description (Posting).

Job Title: Gen AI ArchitectJob Description: We are seeking a highly skilled Generative AI Architect to join our dynamic team and drive the development of advanced AI systems that have capabilities to learn, reason and make decisions autonomously.Key Responsibilities: AI Systems Architecture: Design and develop the architecture and infrastructure for Gen AI systems, including mechanisms for data storage, processing, and retrieval. Ensure the systems scalability, flexibility, and efficiency to handle large algorithms. Algorithm Development: Develop and implement advanced AI algorithms and models, including machine learning, deep learning, and neural networks. Continuously evaluate and improve these algorithms to enhance system performance and accuracy. Data Integration: Identify relevant data sources and design methods for data collection, integration, cleansing, and transformation. Collaborate with data scientists and engineers to ensure the quality and relevance of data for AI model training. Model Training and Evaluation: Train AI models using supervised, unsupervised, or reinforcement learning techniques. Implement evaluation methodologies to measure the performance and effectiveness of trained models. Fine-tune models based on feedback and data insights. Neural Network Design: Design and optimize deep learning neural networks for various AI tasks, such as natural language processing, computer vision, recommendation systems, and predictive analytics. Implement innovative architectures and techniques to improve model accuracy and efficiency. System Integration: Collaborate with software developers and engineers to integrate AI systems into existing platforms or applications. Ensure seamless communication and compatibility between AI components and other software modules. Ethical and Responsible AI: Adhere to ethical AI practices, such as fairness, transparency, and accountability. Address biases and potential risks associated with AI systems to ensure responsible deployment and usage. Research and Innovation: Stay updated with the latest advancements in AI technologies, frameworks, and algorithms. Conduct research and experimentation to explore innovative approaches and techniques that can enhance AI capabilities. Teamwork and Communication: Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to define AI requirements and deliver AI solutions that meet business objectives. Communicate complex AI concepts and solutions effectively to both technical and non-technical audiences. Mandatory Qualifications/Skills: A bachelors or masters degree or equivalent in computer science, Artificial Intelligence, or related field. Experience with large language models (LLMs) and prompt engineering. Experience in designing and developing AI systems, including machine learning, deep learning, and neural networks. Strong programming skills in languages such as Python, R, or Java Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or Keras. Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms. Solid understanding of AI concepts, algorithms, and methodologies. Knowledge of designing large scale AI solutions, data integration, cleansing, and transformation techniques. Excellent problem-solving and analytical skills, with the ability to think creatively and provide innovative solutions. Strong communication and collaboration skills to work effectively in multidisciplinary teams. Knowledge of ethical AI practices and laws is a plus. Preferred Skills : Knowledge of NVIDIA CUDA, cuDNN, TensorR

ET - Senior Group Technical Architect

Job Description (Posting).

Job Title: Gen AI ArchitectJob Description: We are seeking a highly skilled Generative AI Architect to join our dynamic team and drive the development of advanced AI systems that have capabilities to learn, reason and make decisions autonomously.Key Responsibilities: AI Systems Architecture: Design and develop the architecture and infrastructure for Gen AI systems, including mechanisms for data storage, processing, and retrieval. Ensure the systems scalability, flexibility, and efficiency to handle large algorithms. Algorithm Development: Develop and implement advanced AI algorithms and models, including machine learning, deep learning, and neural networks. Continuously evaluate and improve these algorithms to enhance system performance and accuracy. Data Integration: Identify relevant data sources and design methods for data collection, integration, cleansing, and transformation. Collaborate with data scientists and engineers to ensure the quality and relevance of data for AI model training. Model Training and Evaluation: Train AI models using supervised, unsupervised, or reinforcement learning techniques. Implement evaluation methodologies to measure the performance and effectiveness of trained models. Fine-tune models based on feedback and data insights. Neural Network Design: Design and optimize deep learning neural networks for various AI tasks, such as natural language processing, computer vision, recommendation systems, and predictive analytics. Implement innovative architectures and techniques to improve model accuracy and efficiency. System Integration: Collaborate with software developers and engineers to integrate AI systems into existing platforms or applications. Ensure seamless communication and compatibility between AI components and other software modules. Ethical and Responsible AI: Adhere to ethical AI practices, such as fairness, transparency, and accountability. Address biases and potential risks associated with AI systems to ensure responsible deployment and usage. Research and Innovation: Stay updated with the latest advancements in AI technologies, frameworks, and algorithms. Conduct research and experimentation to explore innovative approaches and techniques that can enhance AI capabilities. Teamwork and Communication: Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to define AI requirements and deliver AI solutions that meet business objectives. Communicate complex AI concepts and solutions effectively to both technical and non-technical audiences. Mandatory Qualifications/Skills: A bachelors or masters degree or equivalent in computer science, Artificial Intelligence, or related field. Experience with large language models (LLMs) and prompt engineering. Experience in designing and developing AI systems, including machine learning, deep learning, and neural networks. Strong programming skills in languages such as Python, R, or Java Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or Keras. Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms. Solid understanding of AI concepts, algorithms, and methodologies. Knowledge of designing large scale AI solutions, data integration, cleansing, and transformation techniques. Excellent problem-solving and analytical skills, with the ability to think creatively and provide innovative solutions. Strong communication and collaboration skills to work effectively in multidisciplinary teams. Knowledge of ethical AI practices and laws is a plus. Preferred Skills : Knowledge of NVIDIA CUDA, cuDNN, TensorR

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ET - Senior Group Technical Architect

Job Description (Posting).

Job Title: Gen AI ArchitectJob Description: We are seeking a highly skilled Generative AI Architect to join our dynamic team and drive the development of advanced AI systems that have capabilities to learn, reason and make decisions autonomously.Key Responsibilities: AI Systems Architecture: Design and develop the architecture and infrastructure for Gen AI systems, including mechanisms for data storage, processing, and retrieval. Ensure the systems scalability, flexibility, and efficiency to handle large algorithms. Algorithm Development: Develop and implement advanced AI algorithms and models, including machine learning, deep learning, and neural networks. Continuously evaluate and improve these algorithms to enhance system performance and accuracy. Data Integration: Identify relevant data sources and design methods for data collection, integration, cleansing, and transformation. Collaborate with data scientists and engineers to ensure the quality and relevance of data for AI model training. Model Training and Evaluation: Train AI models using supervised, unsupervised, or reinforcement learning techniques. Implement evaluation methodologies to measure the performance and effectiveness of trained models. Fine-tune models based on feedback and data insights. Neural Network Design: Design and optimize deep learning neural networks for various AI tasks, such as natural language processing, computer vision, recommendation systems, and predictive analytics. Implement innovative architectures and techniques to improve model accuracy and efficiency. System Integration: Collaborate with software developers and engineers to integrate AI systems into existing platforms or applications. Ensure seamless communication and compatibility between AI components and other software modules. Ethical and Responsible AI: Adhere to ethical AI practices, such as fairness, transparency, and accountability. Address biases and potential risks associated with AI systems to ensure responsible deployment and usage. Research and Innovation: Stay updated with the latest advancements in AI technologies, frameworks, and algorithms. Conduct research and experimentation to explore innovative approaches and techniques that can enhance AI capabilities. Teamwork and Communication: Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to define AI requirements and deliver AI solutions that meet business objectives. Communicate complex AI concepts and solutions effectively to both technical and non-technical audiences. Mandatory Qualifications/Skills: A bachelors or masters degree or equivalent in computer science, Artificial Intelligence, or related field. Experience with large language models (LLMs) and prompt engineering. Experience in designing and developing AI systems, including machine learning, deep learning, and neural networks. Strong programming skills in languages such as Python, R, or Java Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or Keras. Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms. Solid understanding of AI concepts, algorithms, and methodologies. Knowledge of designing large scale AI solutions, data integration, cleansing, and transformation techniques. Excellent problem-solving and analytical skills, with the ability to think creatively and provide innovative solutions. Strong communication and collaboration skills to work effectively in multidisciplinary teams. Knowledge of ethical AI practices and laws is a plus. Preferred Skills : Knowledge of NVIDIA CUDA, cuDNN, TensorR

ET - Senior Group Technical Architect

Massachusetts

>11 Years

USA

Job Family

Architecture / Design

No. of Positions

3

Job Description (Posting).

Job Title: Gen AI ArchitectJob Description: We are seeking a highly skilled Generative AI Architect to join our dynamic team and drive the development of advanced AI systems that have capabilities to learn, reason and make decisions autonomously.Key Responsibilities: AI Systems Architecture: Design and develop the architecture and infrastructure for Gen AI systems, including mechanisms for data storage, processing, and retrieval. Ensure the systems scalability, flexibility, and efficiency to handle large algorithms. Algorithm Development: Develop and implement advanced AI algorithms and models, including machine learning, deep learning, and neural networks. Continuously evaluate and improve these algorithms to enhance system performance and accuracy. Data Integration: Identify relevant data sources and design methods for data collection, integration, cleansing, and transformation. Collaborate with data scientists and engineers to ensure the quality and relevance of data for AI model training. Model Training and Evaluation: Train AI models using supervised, unsupervised, or reinforcement learning techniques. Implement evaluation methodologies to measure the performance and effectiveness of trained models. Fine-tune models based on feedback and data insights. Neural Network Design: Design and optimize deep learning neural networks for various AI tasks, such as natural language processing, computer vision, recommendation systems, and predictive analytics. Implement innovative architectures and techniques to improve model accuracy and efficiency. System Integration: Collaborate with software developers and engineers to integrate AI systems into existing platforms or applications. Ensure seamless communication and compatibility between AI components and other software modules. Ethical and Responsible AI: Adhere to ethical AI practices, such as fairness, transparency, and accountability. Address biases and potential risks associated with AI systems to ensure responsible deployment and usage. Research and Innovation: Stay updated with the latest advancements in AI technologies, frameworks, and algorithms. Conduct research and experimentation to explore innovative approaches and techniques that can enhance AI capabilities. Teamwork and Communication: Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to define AI requirements and deliver AI solutions that meet business objectives. Communicate complex AI concepts and solutions effectively to both technical and non-technical audiences. Mandatory Qualifications/Skills: A bachelors or masters degree or equivalent in computer science, Artificial Intelligence, or related field. Experience with large language models (LLMs) and prompt engineering. Experience in designing and developing AI systems, including machine learning, deep learning, and neural networks. Strong programming skills in languages such as Python, R, or Java Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or Keras. Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms. Solid understanding of AI concepts, algorithms, and methodologies. Knowledge of designing large scale AI solutions, data integration, cleansing, and transformation techniques. Excellent problem-solving and analytical skills, with the ability to think creatively and provide innovative solutions. Strong communication and collaboration skills to work effectively in multidisciplinary teams. Knowledge of ethical AI practices and laws is a plus. Preferred Skills : Knowledge of NVIDIA CUDA, cuDNN, TensorR

Qualification

B-Tech

Employee Group

Business Line FT

City

Calaveras

Entity

CSW

Auto req ID

1611490BR

Expected Date of Closure

25-Nov-2025

Pay Range Minimum

140000

Pay Range Maximum

180000

Skill (Primary)

Data Science-Artificial Intelligence-Gen AI

Skill Level 3 (Secondary Skill 1)

Technical Skills (ERS)-Other Technical Skills-Pytorch

Skill Level 3 (Secondary Skill 2)

Data Science-Artificial Intelligence-Deep learning

Skill Level 3 (Secondary Skill 3)

Data Science-Advanced Analytics-Python

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Information :

• Company : HCL
• Position : ET - Senior Group Technical Architect
• Location : Calaveras County, CA
• Country : US