AWS SageMaker

Job Description: Job Title: AWS SageMaker - Banking Domain Location: Charlotte, NC (Remote for a qualified person) Rate: $65 - $70/hr Position Type: Contract Number of Positions: 2 About the Role: We are seeking two highly skilled and experienced AWS SageMaker to join our team and lead a critical project for a major banking client. The ideal candidate will have a very strong profile, with a deep understanding of AWS SageMaker and a proven track record of leading complex Machine Learning (ML) initiatives from concept to production. This is a client-facing leadership role, requiring a combination of technical expertise, business acumen, and strong communication skills. Key Responsibilities: • Lead the end-to-end design, development, and deployment of machine learning solutions using AWS SageMaker for our banking client. • Serve as the primary technical lead and client-facing expert, translating complex business requirements into scalable and secure ML solutions. • Architect and implement robust MLOps pipelines for automated model training, deployment, monitoring, and retraining. • Collaborate with data scientists, data engineers, and business stakeholders to understand project requirements and deliver solutions that meet business objectives. • Provide technical guidance and mentorship to junior team members, ensuring best practices in ML development and MLOps are followed. • Conduct technical workshops and presentations for the client's internal teams to showcase the value of the solutions and drive adoption. • Ensure solutions adhere to the banking industry's security, compliance, and governance standards. • Stay up-to-date with the latest AWS services, ML frameworks, and industry trends to recommend innovative solutions. Required Qualifications: • 7+ years of experience in data science, machine learning, and/or MLOps. • 5+ years of hands-on experience with AWS SageMaker, including but not limited to SageMaker Studio, Pipelines, Model Registry, and Inference Endpoints. • Proven experience in a client-facing lead or consulting role. • Deep understanding of the banking or financial services domain, with experience applying ML to solve business problems in this sector (e.g., fraud detection, risk modeling, customer churn analysis). • Expertise in building and deploying ML models, including data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation. • Strong proficiency in Python and popular ML/deep learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. • Solid experience with MLOps practices and tools (e.g., MLflow, Kubeflow, CI/CD pipelines). • Experience with other key AWS services such as S3, Lambda, Glue, Step Functions, and IAM. • Excellent communication, presentation, and interpersonal skills. • Ability to work independently and manage project deliverables with a high degree of autonomy. Preferred Qualifications: • AWS Certified Machine Learning – Specialty certification. • Experience with generative AI and large language models (LLMs) on AWS. • Experience with containerization technologies (Docker) and orchestration (Kubernetes/EKS). • Familiarity with Infrastructure as Code (IaC) tools like AWS CloudFormation or Terraform.