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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-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • Minimum of 7.5 years of experience in Snowflake Data Warehouse.
  • A bachelor's degree or equivalent is required.
  • Minimum of 5 years of experience as a machine learning engineer or scientist deploying models in production at scale, including monitoring, alerting, automatic bug filing, and auditing.
  • Minimum of 5 years of experience applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming.
  • Minimum of 3 years of experience in distributed computing systems and architecture, which may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, or distributed networks.
  • Minimum of 2 years of experience building and deploying AI/ML-based software to a cloud environment.
  • Proficiency in Python and Python-based AI/ML frameworks, with familiarity with relevant libraries and frameworks such as TensorFlow and PyTorch.
  • Experience working with language-model APIs and optimizing their usage for specific applications.
  • Experience with Python, C++, Java, R, and SQL.
  • Strong written and verbal communication skills, including the ability to communicate complex technical concepts to non-technical stakeholders.
  • Strong client-facing skills in a consulting environment.
  • Ability to collaborate with internal and client-side teams.
  • Strong understanding of data storage, retrieval, and optimization techniques within cloud-based data warehouse environments.
  • Experience designing scalable data architectures that support large-scale machine learning workloads.
  • Familiarity with data integration and transformation processes to prepare datasets for model training and evaluation.
  • Ability to analyze and troubleshoot complex data workflows to ensure data quality and system reliability.
  • 15 years of full-time education is required.

Responsibilities

  • Formulate real-world problems into practical, efficient, and scalable AI 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.
  • Conduct research and development of AI and high-performance computing algorithms, models, and simulations, and apply them to complex business problems at client sites.
  • Work with large-scale datasets and use data-preprocessing techniques to ensure high-quality inputs 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 structure advanced language models that understand and generate human-like text, and evaluate and refine model parameters to improve natural-language-processing capabilities and performance at scale.
  • Collaborate with teams to integrate language models into broader systems and applications.
  • Collaborate with the team and manage its work as a subject-matter expert.
  • Make decisions for the team and contribute to key decisions across multiple teams.
  • Provide solutions to problems for the immediate team and across multiple teams.
  • Lead the development and implementation of architectural strategies for large language models to meet project goals.
  • Facilitate knowledge sharing and mentorship within the team.
  • Coordinate cross-functional efforts to align language-model architectures with organizational objectives.

Desired Qualifications

  • Experience with data engineering.
  • A master's or PhD in a related field, such as computer science or engineering.

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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