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Generative AI Specialist

Capgemini

Capgemini

Software Engineering, Data Science
United States
Posted on Wednesday, May 22, 2024

Job Title: Generative AI Implementation Specialist

Job Location: Hybrid (preferred base cities - Atlanta, Seattle, Dallas, Houston, Chicago, NYC, and San Fran)

Job Description: The Generative AI Implementation Specialist will be responsible for implementing and deploying advanced generative AI models and systems in various applications and platforms. You will work closely with cross-functional teams to understand project requirements, develop custom solutions, and ensure successful integration of generative AI technologies.

Key Responsibilities:

  • Solution Design: Collaborate with stakeholders to understand project requirements and define objectives for generative AI implementations. Design customized solutions tailored to meet specific business needs and use cases.
  • Model Development: Develop, train, and fine-tune generative AI models using machine learning frameworks and techniques. Optimize models for performance, scalability, and efficiency.
  • Integration: Integrate generative AI models and systems into existing applications, platforms, and workflows. Ensure seamless integration with other software components and data sources.
  • Deployment: Manage the deployment process of generative AI solutions in production environments. Implement monitoring and logging mechanisms to track system performance and detect anomalies.
  • Continuous Learning: Stay up-to-date with the latest advancements in generative AI technologies and best practices. Continuously assess and improve the performance, efficiency, and usability of deployed solutions.
  • Support RAISE in US rollout factor/s

Required Skills:

  • Master’s degree or PhD in Computer Science, Statistics, Economics, Mathematics, or other closely related field.
  • Proven experience in implementing and deploying generative AI models and systems in real-world applications. Experience with natural language processing (NLP) and text generation is a plus.
  • Proficiency in machine learning frameworks and libraries such as TensorFlow, PyTorch, or similar. Strong programming skills in languages like Python, Java, or C++.
  • Solid understanding of software development methodologies, DevOps practices, and version control systems (e.g., Git).
  • Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
  • Experience working with vector databases, synthetic data and Trustworthy components.
  • Client experience deploying large scale IoT / Supply Chain AI engagements globally

Life at Capgemini

Capgemini supports all aspects of your well-being throughout the changing stages of your life and career. For eligible employees, we offer:

  • Flexible work
  • Healthcare including dental, vision, mental health, and well-being programs
  • Financial well-being programs such as 401(k) and Employee Share Ownership Plan
  • Paid time off and paid holidays
  • Paid parental leave
  • Family building benefits like adoption assistance, surrogacy, and cryopreservation
  • Social well-being benefits like subsidized back-up child/elder care and tutoring
  • Mentoring, coaching and learning programs
  • Employee Resource Groups
  • Disaster Relief

About Capgemini

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of €22.5 billion.

Get The Future You Want | www.capgemini.com

Disclaimer

Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodations do not pose an undue hardship.

Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Click the following link for more information on your rights as an Applicant http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Applicants for employment in the US must have valid work authorization that does not now and/or will not in the future require sponsorship of a visa for employment authorization in the US by Capgemini.


Job Title: Generative AI Implementation Specialist

Job Location: Hybrid (preferred base cities - Atlanta, Seattle, Dallas, Houston, Chicago, NYC, and San Fran)

Job Description: The Generative AI Implementation Specialist will be responsible for implementing and deploying advanced generative AI models and systems in various applications and platforms. You will work closely with cross-functional teams to understand project requirements, develop custom solutions, and ensure successful integration of generative AI technologies.

Key Responsibilities:

  • Solution Design: Collaborate with stakeholders to understand project requirements and define objectives for generative AI implementations. Design customized solutions tailored to meet specific business needs and use cases.
  • Model Development: Develop, train, and fine-tune generative AI models using machine learning frameworks and techniques. Optimize models for performance, scalability, and efficiency.
  • Integration: Integrate generative AI models and systems into existing applications, platforms, and workflows. Ensure seamless integration with other software components and data sources.
  • Deployment: Manage the deployment process of generative AI solutions in production environments. Implement monitoring and logging mechanisms to track system performance and detect anomalies.
  • Continuous Learning: Stay up-to-date with the latest advancements in generative AI technologies and best practices. Continuously assess and improve the performance, efficiency, and usability of deployed solutions.
  • Support RAISE in US rollout factor/s

Required Skills:

  • Master’s degree or PhD in Computer Science, Statistics, Economics, Mathematics, or other closely related field.
  • Proven experience in implementing and deploying generative AI models and systems in real-world applications. Experience with natural language processing (NLP) and text generation is a plus.
  • Proficiency in machine learning frameworks and libraries such as TensorFlow, PyTorch, or similar. Strong programming skills in languages like Python, Java, or C++.
  • Solid understanding of software development methodologies, DevOps practices, and version control systems (e.g., Git).
  • Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
  • Experience working with vector databases, synthetic data and Trustworthy components.
  • Client experience deploying large scale IoT / Supply Chain AI engagements globally