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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-timeKolkata, West Bengal, IndiaNo salary listed

About the Job

Requirements

  • A bachelor's degree or equivalent is required.
  • At least 12 years of experience in 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 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 explain complex technical concepts to non-technical stakeholders.
  • Strong client-facing skills in a consulting environment.
  • Ability to collaborate with a variety of internal and client-side teams.
  • Proficiency in designing and optimizing neural network architectures for natural language processing.
  • Experience with large-scale data processing and management in cloud environments.
  • Ability to analyze and improve model training processes using extensive unlabeled datasets.
  • Familiarity with integrating language models into production systems and ensuring their scalability and 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 to use cases based on business needs, data availability, system and infrastructure requirements, including edge devices and high-performance computing.
  • Engage in 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 UI designers, to achieve end-to-end project goals and integrate solutions into production.
  • Design, build, and operationalize AI and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes.
  • Assess client needs and data, select and customize models, design scalable data and MLOps/LLMOps pipelines for training and production, and ensure deployed systems' quality, value, and reliability.
  • Analyze model performance and refine model parameters.
  • Lead the development and implementation of scalable language model architectures to meet project goals.
  • Manage and coordinate the team's work, and take responsibility for team decisions.
  • Engage with multiple teams and contribute to key decisions.
  • Provide solutions to problems that apply across multiple teams.
  • Facilitate knowledge sharing and mentorship within the team.
  • Coordinate cross-functional efforts to align model development with organizational objectives.

Desired Qualifications

  • Experience with Snowflake Data Warehouse.
  • Experience with Microsoft Azure Data Services.
  • A master's degree or PhD in a related field, with computer science and engineering given as examples.

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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