Machine Learning Engineer

Join Our Team: Machine Learning Engineer at Capgemini

Shape the Future with AI

Are you a talented and innovative Machine Learning Engineer looking to make a tangible impact? At Capgemini, you’ll join a global community where you’re empowered to shape your career, collaborate across borders, and reimagine what’s possible. Join us as we partner with the world’s leading organizations to unlock the value of technology, driving both digital transformation and a more sustainable, inclusive world.

The Opportunity: Bringing ML to Life

Transforming Models into Production Solutions

We’re seeking a dedicated Machine Learning Engineer to play a critical role in taking cutting-edge AI/ML models from development to scalable, robust production environments. You’ll be instrumental in building the infrastructure and pipelines that power our clients’ most innovative solutions, ensuring seamless integration and performance.

What You’ll Do

Key Responsibilities

As a Machine Learning Engineer on our team, you will:

• Architect and Build Production ML Systems: Design, develop, and implement scalable, reliable pipelines for deploying machine learning models into real-world applications and services.
• Manage Cloud Infrastructure: Establish and maintain robust cloud-based environments (leveraging platforms like AWS, GCP, or Azure) required for the entire ML lifecycle, from training to deployment.
• Automate and Optimize MLOps: Utilize and integrate MLOps tools (e.g., MLflow, SageMaker, Kubeflow) to automate workflows, improve efficiency, and ensure consistency in the ML development and deployment process.
• Ensure Seamless Integration: Work closely with development and operations teams to ensure ML solutions are smoothly integrated and performant in production.
• Monitor and Maintain: Implement effective monitoring and logging strategies to track model performance, system health, and troubleshoot issues in live environments.

What You’ll Bring

Qualifications & Experience

We’re looking for candidates with a strong foundation in ML engineering and a passion for putting models into practice. Your background should include:

• Proven expertise in Python programming, coupled with hands-on experience using popular ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Practical experience working with major cloud platforms (AWS, GCP, or Azure) and containerization technologies like Docker and Kubernetes.
• Familiarity with key MLOps tools and practices (e.g., MLflow, SageMaker, Kubeflow).
• Solid understanding of the end-to-end ML lifecycle, including model evaluation, versioning, deployment strategies, and monitoring.
• Experience with monitoring tools and logging frameworks specifically for machine learning systems in production.

Why Capgemini?

Life & Benefits Designed for You

When you join Capgemini, you’re joining a company invested in your success and well-being. We believe in fostering a supportive and inclusive environment where you can thrive both professionally and personally. Eligible employees enjoy a comprehensive benefits package, including:

• Flexible Work Arrangements
• Holistic Well-being Programs: Comprehensive healthcare coverage (medical, dental, vision), mental health support, and wellness initiatives.
• Financial Security: Opportunities like our 401(k) plan and Employee Share Ownership Plan.
• Generous Time Off: Paid time off and company holidays.
• Family Support: Paid parental leave, family building assistance (adoption, surrogacy, etc.), and subsidized back-up care for children/elders.
• Continuous Growth: Access to extensive mentoring, coaching, and learning programs.
• Engaged Community: Participate in our Employee Resource Groups.
• Support through our Disaster Relief programs.

Compensation & Salary Transparency

Understanding Your Potential Earnings

In compliance with state and local regulations, Capgemini is committed to transparency regarding compensation. The base salary range disclosed below represents our good-faith estimate for this role at the time of posting for the tagged location. It reflects a wide array of factors influencing compensation decisions, including experience, skills, qualifications, education, geographic location, and business needs.

The base salary range for this position is $90,000 – $95,000 per year.

While the disclosed range is a guide, actual compensation may vary and could be higher or lower. It is typically not common for individuals to be hired at the very top of the listed range.

In addition to base salary, this role may be eligible for other forms of compensation, such as variable pay, bonuses, or commissions. Full-time regular employees are also eligible for comprehensive benefits, including paid time off, medical/dental/vision insurance, 401(k), and other benefits as outlined in our programs.

Please note: Final compensation decisions are subject to various factors and company discretion, consistent with applicable law. No amount of pay is considered earned until vested and determinable. The amount and availability of any bonus, commission, or other compensation are at the Company’s sole discretion unless and until paid.

About Capgemini

A Global Leader in Business & Technology Transformation

Capgemini is a world-renowned leader, partnering with organizations globally to navigate and accelerate their journey through digital and sustainable transformation. With a rich heritage spanning over 55 years, we empower our clients to unlock the immense value of technology, addressing the full spectrum of their business challenges.

Our diverse team of 340,000 professionals in more than 50 countries delivers end-to-end solutions – from strategy and design to advanced engineering. We leverage market-leading capabilities in areas like AI, Generative AI, Cloud, and Data, combined with deep industry expertise and a robust partner ecosystem, to create tangible impact for both enterprises and society.

Diversity, Inclusion & Equal Opportunity

Our Commitment to a Fair & Inclusive Workplace

Capgemini is a proud Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment.

This posting provides a general overview of the duties, responsibilities, and qualifications for this position. While it may reference physical, mental, sensory, or environmental demands, Capgemini is committed to providing reasonable accommodations to individuals with disabilities to ensure equal employment opportunity, provided such accommodations do not pose an undue hardship.

If you require assistance or accommodation during the recruitment process, please do not hesitate to contact your recruiting representative.

For more information on your rights as an Applicant, please visit: http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

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