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Accenture

Advises businesses and runs their technology

Large Language Model Architect

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeChennai, Tamil Nadu, IndiaNo salary listed

About the Job

Requirements

  • A bachelor's degree or equivalent is required.
  • At least 18 years of experience with Databricks Unified Data Analytics Platform is required.
  • At least 7 years of experience as a machine learning engineer or scientist deploying models in production at scale, including monitoring, alerting, automatic bug filing, and auditing is required.
  • At least 7 years of experience applying theoretical computer science foundations, including computer system architecture, system engineering, and programming, is required.
  • At least 5 years of experience with distributed computing systems and architecture, potentially including big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, or distributed networks, is required.
  • At least 4 years of experience building and deploying AI/ML-based software in a cloud environment is required.
  • Proficiency in Python and Python-based AI/ML frameworks, with familiarity with relevant libraries and frameworks such as TensorFlow and PyTorch, is required.
  • Experience with language model APIs and optimizing their use for specific applications is required.
  • Experience with Python, C++, Java, R, and SQL is required.
  • Strong written and verbal communication skills and the ability to explain complex technical concepts to non-technical stakeholders are required.
  • Strong client-facing skills in a consulting environment are required.
  • The candidate must have completed 15 years of full-time education.
  • Strong expertise in designing and tuning neural network architectures for natural language processing tasks is required.
  • Experience handling large-scale unstructured text datasets and optimizing data pipelines for model training is required.
  • The ability to integrate language models into production environments while ensuring reliability and scalability is required.
  • Familiarity with distributed computing frameworks and cloud-based analytics platforms to support model deployment is required.

Responsibilities

  • Formulate real-world problems into practical, efficient, and scalable artificial intelligence and machine learning solutions.
  • Develop and implement machine learning algorithms, models, and computational systems, and design and build scalable data pipelines to support model training and production with DevOps and MLOps.
  • Customize and apply deep learning and generative AI models for use cases based on business needs, data availability, and system and infrastructure requirements, including edge devices and high-performance computing.
  • Engage in research and development of artificial intelligence and high-performance computing algorithms, models, and simulations, and apply them to complex business problems at client sites.
  • Work with large-scale datasets and apply data preprocessing techniques to ensure high-quality input for training and production.
  • Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools.
  • Justify the value of model approaches for business problems.
  • Collaborate with business and technical teams, including users, use-case representatives, business owners, engineers, architects, and user-interface designers, to achieve end-to-end project goals and integrate solutions into production.
  • Design and develop advanced language models capable of understanding and generating human-like text, envision neural network architectures that process unstructured text, and optimize them for performance and scalability.
  • Collaborate with cross-functional teams to align model capabilities with business objectives and refine model parameters to improve accuracy and efficiency.
  • Lead the development and implementation of scalable language model architectures that meet organizational goals.
  • Collaborate with stakeholders to translate business requirements into technical solutions using large language models.
  • Evaluate emerging technologies and methodologies to improve model performance and maintain competitive advantage.
  • Engage with multiple teams and be responsible for team decisions; provide solutions applicable across multiple teams and business-area problems.

Desired Qualifications

  • An MS or PhD in a related field, such as computer science or engineering, is preferred.
  • Experience with machine learning and data science is preferred.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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