Capgemini

Machine Learning Engineer

Capgemini Colorado, United States

Save

Direct message the job poster from Capgemini

This is a full time ML Engineer requiring you to relocate to Seattle. We will provide 6 weeks of training and continued mentorship.


  • You must live in Seattle otherwise relocate at your own expense to start in March 2026
  • You will have 1 to 2 years working experience after your graduation
  • You are required to be in the office for 3 days per week


Job Description: The Data Scientist/ML Engineer will demonstrate excellent knowledge of ML algorithms (e.g., Linear Regression, Logistic Regression, Clustering/Segmentation, Decision Tree, Random Forest Algorithm, GBM, DNN, Naive Bayes, Support Vector Machine, etc.) to lead efforts, teams, projects, and engage with customers.


KEY RESPONSIBILITIES:

  • Responsible for developing and implementing AI-assisted marketing analytics solutions that address customer needs using data science, machine learning.
  • Work closely with multi-functional teams to deliver innovative solutions that drive business growth and improve customer engagement.


Required Skills:

  • Excellent knowledge of ML algorithms (e.g., Linear Regression, Logistic Regression, Clustering/Segmentation, Decision Tree, Random Forest Algorithm, GBM, DNN, Naive Bayes, Support Vector Machine, etc.)
  • Expertise in applying statistical, sophisticated analytics, machine learning, and/or AI, deep learning concepts, and techniques to solve business problems. Strong programming skills using Python, SQL, PySpark
  • Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn
  • Strong analytical, critical-thinking skills with proven ability to identify/analyze/synthesize data and use the data to drive decisions
  • Superior communication and persuasion skills, talent for storytelling, visualization, and crafting insights from data to deliver practical recommendations for business action
  • Good knowledge of calculus, linear algebra, statistics, and probability
  • Master’s degree in Math, Statistics, Data Science, Analytics, Econometrics, Computer science, Operations Research, Behavioral Science, or another analytical/quantitative field required


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


Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.


Make it real | www.capgemini.com

  • Seniority level

    Associate
  • Employment type

    Full-time
  • Job function

    Information Technology
  • Industries

    Outsourcing and Offshoring Consulting and Business Consulting and Services

Referrals increase your chances of interviewing at Capgemini by 2x

See who you know
Get notified when a new job is posted.

Similar jobs

People also viewed

Similar Searches

Explore collaborative articles

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

Explore More