GenAI & AI/ML Framework Specialist

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.

Job Location : New York, NY / Arlington, VA (Onsite/Hybrid from Day 1) Job Description We are seeking a highly skilled GenAI & AI/ML Framework Specialist to design, develop, and scale next-generation Artificial Intelligence solutions. This role will focus on building advanced machine learning and Generative AI applications, optimizing open-source AI frameworks, and integrating AI-powered capabilities into enterprise platforms.

The ideal candidate will possess deep expertise in AI/ML frameworks, Large Language Models (LLMs), MLOps, cloud platforms, and modern data infrastructure. You will work closely with product, engineering, and data science teams to deliver high-performance, production-ready AI solutions that drive business value.

Key Responsibilities

• Design and implement Generative AI solutions using LLMs, RAG, prompt engineering, and fine-tuning techniques.
• Develop, train, and optimize machine learning and deep learning models.
• Build scalable AI/ML pipelines for data processing, model training, and deployment.
• Integrate AI models into enterprise applications and production environments.
• Improve model inference performance, scalability, and cost efficiency.
• Collaborate with cross-functional teams to deliver AI-driven business solutions.

Required Skills

• Expertise in PyTorch, TensorFlow, or JAX.
• Hands-on experience with Hugging Face, LangChain, LlamaIndex, and vLLM.
• Strong Python programming skills.
• Solid understanding of machine learning, deep learning, Transformers, CNNs, and RLHF.
• Experience with vector databases (Pinecone, ChromaDB, Milvus) and SQL/NoSQL databases.
• Knowledge of MLOps tools such as MLflow, Kubeflow, or Triton Inference Server.
• Experience with cloud platforms such as AWS SageMaker, Azure AI, or GCP Vertex AI, and GPU acceleration (CUDA).

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related quantitative discipline.
• Minimum 8 years of experience in Data Science, Machine Learning Engineering, or AI Engineering.
• At least 2 years of hands-on experience in Generative AI, including LLM-based solutions and enterprise AI deployments.
• Proven experience designing, developing, and deploying production-grade AI/ML applications.
• Strong analytical, problem-solving, and communication skills.
• Ability to collaborate effectively in a fast-paced, cross-functional environment.

Preferred Qualifications

• Experience with enterprise-scale AI transformation initiatives.
• Knowledge of model governance, responsible AI, and AI security frameworks.
• Experience working with multi-modal AI applications involving text, image, audio, or video models.
• Exposure to distributed training, model compression, quantization, and inference optimization techniques.
• Familiarity with agentic AI architectures and autonomous workflow orchestration.

The base compensation range for this role in the posted location is: 85786- 105237

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, …