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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

  • A Bachelor's degree or equivalent is required.
  • At least 7.5 years of experience with Google Cloud Data Services is required.
  • At least 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.
  • At least 5 years of experience applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming.
  • At least 3 years of experience with distributed computing systems and architecture, which may include big data, high-performance computing, engineering simulations, scientific computing, grid and cloud computing, and distributed networks.
  • At least 2 years of experience building and deploying artificial intelligence and machine learning software to a cloud environment.
  • Proficiency in Python and Python-based artificial intelligence and machine learning frameworks, with familiarity with relevant libraries and frameworks such as TensorFlow and PyTorch.
  • Experience working with large language model application programming interfaces and optimizing their use 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.
  • Strong cross-functional collaboration skills with internal and client-side teams.
  • Fifteen years of full-time education 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 artificial intelligence models for use cases based on business needs, data availability, system and infrastructure requirements, including edge devices and high-performance computing.
  • Research and develop 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 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 capable of understanding and generating natural-language text, including architecting neural networks trained on extensive datasets and refining model parameters.
  • Lead the development and implementation of scalable language-model architectures to meet project goals.
  • Manage the team and take responsibility for team decisions.
  • Engage with multiple teams and contribute to key decisions.
  • Provide solutions to problems for the immediate team and across multiple teams.
  • Facilitate knowledge sharing and mentorship within the team to enhance technical capabilities.
  • Coordinate cross-functional efforts to align language-model development with organizational objectives.
  • Design and optimize neural-network architectures for natural-language processing.
  • Process and manage large-scale data in cloud environments.
  • Analyze and improve model performance through parameter tuning and data handling.
  • Integrate language models into production systems and workflows.

Desired Qualifications

  • A Master's or PhD in a related field, such as computer science or engineering, is preferred.
  • Experience with Snowflake Data Warehouse and Microsoft Azure Data Services is desirable.

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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