AI Solutions Developer

AI Solutions Developer

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.

We are seeking a highly skilled AI Solutions Developer with strong expertise in building end to end AI/ML applications using Python and modern AI frameworks such as Lang Chain, PyTorch, and Tensor Flow. The role involves designing, developing, and deploying intelligent solutions including LLM powered applications, machine learning models, automation pipelines, and AI driven integrations.

Responsibilities:

• AI/ML Model Development:
  Design, build, and optimize machine learning and deep learning models using PyTorch, Tensor Flow, and related frameworks.
• LLM Generative AI Solutions:
  Develop applications powered by Large Language Models using Lang Chain, vector databases, embeddings, and prompt orchestration frameworks.
• Python Based Application Development:
  Build scalable AI services, automation tools, and backend components using Python.
• Data Engineering Pipelines:
  Prepare, transform, and manage datasets, build feature pipelines, and model training workflows.
• Model Deployment MLOps:
  Deploy models into production using APIs, containerization, Docker, CICD, and cloud platforms.
• Evaluation Optimization:
  Perform model tuning, evaluation, and performance optimization to ensure accuracy, efficiency, and reliability.
• Cross Functional
  
  Collaboration:
  
  Work closely with product engineering and business teams to translate strategic requirements into AI driven technical solutions.
• Experimentation Research:
  Stay up to date with emerging AI technologies, evaluate new tools, and prototype innovative solutions.

Required Skills:

• Strong hands on experience with Python for AI/ML development.
• Proficiency with PyTorch, Tensor Flow, or similar deep learning frameworks.
• Experience developing LLM based applications using Lang Chain, embeddings, vector databases, FAISS, Chroma, Pinecone, or similar technologies.
• Ability to design and implement end to end ML pipelines, training, validation, deployment.
• Strong understanding of machine learning concepts, NLP, and deep learning architectures.
• Solid experience with APIs, microservices, and cloud based deployment.
• Strong analytical, debugging, and problem solving skills.

The base compensation range for this role in the posted location is: 56,186 - 87,556. 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.

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

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