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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 5 years of experience in Google Cloud Data Services is required.
  • At least 3 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 3 years of experience applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming.
  • At least 1 year of experience with distributed computing systems and architecture, which may include big data, high-performance computing, engineering simulations, scientific computing, grid and cloud computing, or distributed networks.
  • At least 1 year of experience building and deploying AI/ML-based software in 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 and the ability to explain 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.
  • 15 years of full-time education is required.

Responsibilities

  • 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 including deep learning, generative AI, and large language models, design scalable data and DevOps and MLOps pipelines for training and production, and ensure quality, value, and reliability of deployed systems.
  • 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, and 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 their applications to solve 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 and structure advanced language models capable of understanding and generating natural language; plan neural network configurations and manage extensive datasets to support model performance.
  • Continuously evaluate and refine model architectures to meet project goals, coordinating with teams on technical strategies and deliverables.
  • Collaborate with and manage the team to perform, and take responsibility for team decisions.
  • Engage with multiple teams and contribute to key decisions; provide solutions for the immediate team and across multiple teams.
  • Lead development and implementation of architectural strategies for large language models.
  • Facilitate knowledge sharing and mentorship within the team.
  • Coordinate cross-functional efforts to align project objectives and technical standards.
  • Design and optimize neural network architectures for natural language processing.
  • Integrate cloud-based data services to support scalable machine learning workflows.
  • Work with distributed computing environments and tune performance for model training.

Desired Qualifications

  • Experience with Snowflake Data Warehouse.
  • Experience with Microsoft Azure Data Services.
  • 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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