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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.
  • At least 12 years of experience with the Databricks Unified Data Analytics Platform.
  • 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, systems 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.
  • Experience designing and optimizing neural network architectures for natural language processing tasks.
  • Strong understanding of data-processing pipelines and handling large-scale unstructured datasets.
  • Familiarity with cloud-based analytics platforms and scalable computing environments.
  • Strong written and verbal communication skills and 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 across functions.
  • Fifteen 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.
  • 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.
  • Research and develop 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 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 stakeholders, 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 text, including developing neural-network configurations and optimizing parameters for large amounts of unstructured text data.
  • Continuously refine model architectures to improve performance and scalability, aligning models with project goals and real-world applications.
  • Lead the development and implementation of architectural strategies for large language models to align with organizational objectives.
  • Manage and coordinate the team, make team decisions, engage with multiple teams on key decisions, and provide solutions to problems that apply across teams.
  • Facilitate knowledge sharing and mentorship within the team, and guide junior team members in problem-solving.
  • Coordinate cross-functional efforts to integrate language models into broader systems and workflows.

Desired Qualifications

  • Experience with machine learning and data science.
  • 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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