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Accenture

Advises businesses and runs their technology

Large Language Model Architect

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listed

About the Job

Requirements

  • Proficiency in Databricks Unified Data Analytics Platform.
  • At least 7.5 years of experience with 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, system engineering, and programming.
  • At least 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.
  • 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, and familiarity with relevant libraries and frameworks such as TensorFlow and PyTorch.
  • Experience working with language model APIs and optimizing their use for specific applications.
  • Experience with Python, C++, Java, R, and SQL.
  • Strong expertise in designing and optimizing neural network architectures for natural language processing applications.
  • Experience handling large-scale datasets and implementing efficient data processing pipelines.
  • Ability to troubleshoot and resolve complex technical challenges related to model training and deployment.
  • Familiarity with distributed computing environments and cloud-based analytics platforms.
  • A Bachelor's degree or equivalent.
  • 15 years of full-time education.
  • 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 a variety of internal and client-side teams.

Responsibilities

  • Architect large language models that can process and generate natural language, including designing neural network parameters trained on large quantities of unlabeled text data.
  • Design, build, and operationalize artificial intelligence 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, and design scalable data and MLOps/LLMOps pipelines for training and production while ensuring 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 for 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 new AI and high-performance computing algorithms, models, and simulations, and their applications 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 in 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 human-like text, plan neural network configurations, and manage training using extensive datasets.
  • Continuously evaluate and refine model architectures to improve performance and applicability across natural language processing tasks.
  • Collaborate with cross-functional teams to align model capabilities with project goals and deliver robust, scalable language solutions.
  • 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 to problems for the immediate team and across multiple teams.
  • Lead the development and implementation of innovative language model architectures to meet evolving project requirements.
  • Facilitate knowledge sharing and mentorship within the team.
  • Coordinate with stakeholders to align model design with business objectives and technical feasibility.

Desired Qualifications

  • Experience with machine learning.
  • Experience with 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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