AI Engineer

Capgemini is seeking an AI Engineer in Atlanta, GA to design and deploy production-grade AI solutions. The role focuses on building capabilities across conversational AI, LLMs, NLP, and machine learning, including GenAI implementation such as RAG, performance optimization, and troubleshooting of AI applications.

Key Responsibilities

• Design and develop AI systems for targeted use cases across industries.
• Build algorithms and machine learning models to address specific business challenges.
• Collaborate with cross-functional teams, working with data scientists, product managers, and stakeholders to align AI solutions with business objectives.
• Build and train machine learning models using tools such as TensorFlow and PyTorch, including model development for NLP, computer vision, and robotics.
• Optimize AI performance by tuning models based on statistical analysis and large data sets.
• Implement automation through AI-driven solutions that streamline workflows and improve decision-making.
• Explore AI advancements to incorporate new technologies and frameworks that improve functionality and scalability.
• Troubleshoot and improve AI applications to enhance both performance and user experience.
• Develop AI prototypes to create initial versions for testing and feedback prior to full-scale deployment.

Required Qualifications

• Expertise in conversational AI, LLMs, NLP, and machine learning, including experience training, building, and deploying production AI solutions.
• 5+ years of hands-on experience in AI development, data analysis, and machine learning techniques, including experience putting machine learning models into production.
• Experience using MLflow or similar tools for machine learning lifecycle management.
• Advanced knowledge of machine learning models and large language models (LLMs), including experience using langchain or a similar tool.
• Experience implementing LLMs using vector-based approaches and Retrieval-Augmented Generation (RAG), including model tuning.
• Experience with GPTs, Llama, or other LLM technologies.
• Ability to perform solution architecture validation for LLM solutions.
• Experience putting Generative AI (GenAI) models into production and supporting them.
• Familiarity with cloud platforms such as AWS, Google Cloud, or Azure for deployment and scaling.
• In MLOps roles, ability to write clean, efficient, and reusable code is essential.

Technologies

• MLflow
• langchain
• Retrieval-Augmented Generation (RAG)
• GPTs
• Llama
• AWS
• Google Cloud
• Azure
• TensorFlow
• PyTorch

Compensation

Base compensation range for the posted location: $90,000 to $96,665 per year.

Benefits

• Paid time off based on employee grade (A-F) per policy: Vacation 12-25 days depending on grade, company paid holidays, personal days, and sick leave.
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada).
• Retirement savings plans (for example, 401(k) in the U.S. or RRSP in Canada).
• Life and disability insurance.
• Employee assistance programs.