Capgemini

Data Scientist/ AI Engineer

Capgemini$90K — $160K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree or higher in AI, Machine Learning, Computer Science, or related field.
  • 3-5 years of experience in AI, Machine Learning, Data Science, or Application Development.
  • Hands-on expertise in Generative AI and Machine Learning technologies.
  • Proficiency in Python and development on cloud platforms.
  • Experience with MLOps, model monitoring, and production AI deployments.

Responsibilities

  • Develop and deploy Generative and Predictive AI solutions.
  • Design and integrate AI applications using cloud-based architectures.
  • Build and support AI agents and autonomous systems.
  • Monitor and optimize AI models in production using MLOps.
  • Design and maintain data pipelines, lakes, and warehouses.
  • Troubleshoot model performance and manage data/model drift.
  • Collaborate with teams to align AI solutions with business objectives.

Benefits

  • Paid time off based on employee grade, including vacation, holidays, personal days, and sick leave.
  • Medical, dental, and vision coverage.
  • Retirement savings plans (e.g., 401(k) in the U.S.).
  • Life and disability insurance.
  • Employee assistance programs.
Full Job Description
Location

San Francisco CA

Your Role

The GenAI Engineer / Data Scientist is responsible for designing, developing, deploying, and maintaining Generative AI (GenAI) and Predictive AI solutions that deliver business value. The role requires expertise in AI/ML, cloud platforms, APIs, data engineering, MLOps, and AI agent workflows, with a strong focus on production-grade AI implementation.

Key Responsibilities

Develop and deploy Generative AI solutions (GPT, Claude, Stable Diffusion) and Predictive AI models (regression, classification, clustering).
Design and integrate AI applications using REST APIs, authentication mechanisms, JSON services, and cloud-based architectures.
Build and support AI agents, autonomous systems, and agentic workflows.
Deploy, monitor, and optimize AI models in production using MLOps practices.
Design and maintain data pipelines, data lakes, and data warehouses.
Monitor model performance, troubleshoot issues, and manage data/model drift.
Collaborate with business and technical teams to align AI solutions with organizational objectives.
Create reusable assets, demos, and proof-of-concepts to support innovation and business development.

Required Skills and Experience

A hands-on AI professional with strong expertise in Generative AI, Machine Learning, Python, Cloud Technologies, APIs, MLOps, Data Engineering, and AI Agents, capable of building and scaling enterprise-grade AI solutions from development to production.
Bachelor's degree or higher in AI, Machine Learning, Computer Science, or related field.
3-5 years of experience in AI, Machine Learning, Data Science, or Application Development.
Experience with production AI deployments, MLOps, model monitoring, and cloud platforms.

GPT, Claude LLM, Stable Diffusion
LangChain
TensorFlow
PyTorch
Scikit-learn
RAG (Retrieval-Augmented Generation)
AI Agents & Agentic Workflows
API Development
REST APIs
JSON
HTTP Requests
Authentication & Tokens
Error Handling & Debugging

The base compensation range for this role in the posted location is $90,000- $160,000

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.

About Capgemini

Capgemini is a global leader in consulting, digital transformation, technology and engineering services. The company is headquartered in Paris, France and operates in over 50 countries. Capgemini provides a range of services including strategy and transformation, application services, technology services, and engineering services. The company serves clients in a variety of industries including automotive, consumer products, financial services, healthcare, and retail.
Learn more about Capgemini
Industry
Founded
1967
NASDAQ

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