Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Location: Westlake, TX Job Description Key Skills - Expertise in AI (conversational AI), LLMs, NLP, and machine learning, with experience training, building and deploying production AI solutions. 5+ years of hands-on experience in AI development, data analysis, and machine learning techniques and experience putting Machine Learning models into production. MLOps tools: Experience using Mlflow or similar tools for lifecycle management of machine learning models. Machine Learning Models: Advanced knowledge in Machine Learning models and Large Language Models (LLM), using langchain or a similar tool. LLM Implementation: Experience in implementing LLMs using vector bases and Retrieval-Augmented Generation (RAG), as well as tuning models. Using GPTs, Llama, or any other LLM Solution Architecture Validation: Ability to perform solution architecture validations for LLMs. GenAIOps: Experience in putting Generative AI (GENAI) models into production and providing support to them. Experience with Cloud Computing: Familiarity with cloud computing platforms such as AWS, Google Cloud, or Azure for model deployment and scaling. Software Engineering Skills: The ability to write clean, efficient, and reusable code is essential in MLOps roles. Designs and develops AI systems. Builds algorithms and machine learning models to solve specific challenges across industries. Collaborates with cross-functional teams. Works with data scientists, product managers, and stakeholders to align AI solutions with business objectives. Builds and trains machine learning models. Utilizes tools like TensorFlow and PyTorch to create models for tasks such as NLP, computer vision, and robotics. Optimizes performance. Ensures AI models operate efficiently, making adjustments based on statistical analysis and large data sets. Implements automation. Develops AI-driven solutions to streamline workflows and improve decision-making. Explores advancements in AI. Stays up to date with the latest technologies and frameworks to enhance the functionality and scalability of AI systems. Troubleshoots and improves AI applications. Resolves issues and optimizes systems for better performance and user experience. Develops AI prototypes. Builds initial versions of AI applications for testing and feedback before full-scale deployment. The base compensation range for this role in the posted location is: $90000 to $96665 Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) • Life and disability insurance • Employee assistance programs • Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. 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 accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. 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. Click the following link for more information on your rights as an Applicant in the United States. capgemini.com 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, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

Requirements

Must-haves

Location: Westlake, TX
Key Skills - Expertise in AI (conversational AI), LLMs, NLP, and machine learning, with experience training, building and deploying production AI solutions.
5+ years of hands-on experience in AI development, data analysis, and machine learning techniques and experience putting Machine Learning models into production.
MLOps tools: Experience using Mlflow or similar tools for lifecycle management of machine learning models.
Machine Learning Models: Advanced knowledge in Machine Learning models and Large Language Models (LLM), using langchain or a similar tool.
LLM Implementation: Experience in implementing LLMs using vector bases and Retrieval-Augmented Generation (RAG), as well as tuning models. Using GPTs, Llama, or any other LLM
Solution Architecture Validation: Ability to perform solution architecture validations for LLMs. GenAIOps: Experience in putting Generative AI (GENAI) models into production and providing support to them.
Experience with Cloud Computing: Familiarity with cloud computing platforms such as AWS, Google Cloud, or Azure for model deployment and scaling.
Software Engineering Skills: The ability to write clean, efficient, and reusable code is essential in MLOps roles.
Designs and develops AI systems. Builds algorithms and machine learning models to solve specific challenges across industries.
Collaborates with cross-functional teams. Works with data scientists, product managers, and stakeholders to align AI solutions with business objectives.
Builds and trains machine learning models. Utilizes tools like TensorFlow and PyTorch to create models for tasks such as NLP, computer vision, and robotics.
Optimizes performance. Ensures AI models operate efficiently, making adjustments based on statistical analysis and large data sets.
Implements automation. Develops AI-driven solutions to streamline workflows and improve decision-making.
Explores advancements in AI. Stays up to date with the latest technologies and frameworks to enhance the functionality and scalability of AI systems.
Troubleshoots and improves AI applications. Resolves issues and optimizes systems for better performance and user experience.
Develops AI prototypes. Builds initial versions of AI applications for testing and feedback before full-scale deployment.
The base compensation range for this role in the posted location is: $90000 to $96665
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
Life and disability insurance
Other benefits as provided by local policy and eligibility

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningllmawsazureaccessibility

Platform: successfactors
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off