AI/ML Engineer with AWS SageMaker

Position Title : AI/ML Engineer with AWS SageMaker

Location : Dallas, TX/ Charlotte, NC/ Malvern, PA (Onsite/Hybrid)

Experience : 8 Years

Employee Type : Full Time with Benefits

Job Description

We are seeking a highly experienced AI/ML Engineer with deep expertise in AWS SageMaker, end-to-end machine learning pipeline development, and strong proficiency in Python or R. In this role, you will architect, build, deploy, and optimize scalable machine learning solutions for complex business problems across our U.S. teams.

You will collaborate with cross-functional stakeholders—including data scientists, software engineers, product managers, and cloud engineering teams—to deliver robust ML platforms and cutting-edge AI models in a production environment.

Must Have skills:

• 10 years of experience in Machine Learning, Data Science, or AI engineering roles.
• Advanced proficiency in Python or R (Python strongly preferred).
• Hands-on experience with AWS SageMaker (training jobs, endpoints, pipeline automation, feature store, model registry).
• Strong background in ML model development: regression, classification, time-series, NLP, deep learning, etc.
• Experience working with AWS cloud services such as S3, Lambda, ECS/EKS, Glue, Redshift, IAM, CloudWatch.
• Proven experience building and scaling ML pipelines in production environments.
• Skilled in using ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn, XGBoost, etc.).
• Strong understanding of MLOps practices, automated deployment, containers, and versioning.
• Experience with REST APIs, microservices, and containerization (Docker, Kubernetes).
• Excellent communication and stakeholder management skills.

Key Responsibilities:

• Design, develop, and deploy machine learning models using AWS SageMaker (training, hosting, pipelines, model registry).
• Build and optimize end-to-end ML pipelines, including data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
• Implement automation for CI/CD of ML solutions using tools such as SageMaker Pipelines, AWS CodePipeline, CodeBuild, or similar.
• Collaborate with data engineering teams to build scalable data architectures (Lake Formation, Glue, EMR, Redshift, etc.).
• Develop high-quality, reusable, and modular ML code in Python or R.
• Optimize model performance, inference latency, cost efficiency, and monitoring in production.
• Maintain and improve MLOps best practices, including model governance, versioning, and reproducibility.
• Work with distributed systems and large-scale datasets for training and inference.
• Evaluate new AI/ML technologies, frameworks, and cloud capabilities to enhance the ML platform.
• Drive technical leadership, mentorship, and thought leadership across AI/ML teams.

If your Interested, Kindly, share us your resume on abuzar.umar@capgemini.com

Life At Capgemini

Capgemini supports all aspects of your well-being throughout the changing stages of your life and career. For eligible employees, we offer:

• Flexible work
• Healthcare including dental, vision, mental health, and well-being programs
• Financial well-being programs such as 401(k) and Employee Share Ownership Plan
• Paid time off and paid holidays
• Paid parental leave
• Family building benefits like adoption assistance, surrogacy, and cryopreservation
• Social well-being benefits like subsidized back-up child/elder care and tutoring
• Mentoring, coaching and learning programs
• Employee Resource Groups
• Disaster Relief

Disclaimer

Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodations do not pose an undue hardship.

Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Click the following link for more information on your rights as an Applicant http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law