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Job Title: Sr. Machine Learning Engineer (Strong SageMaker Experience)
Location: Malvern PA
Work Model: Hybrid (Onsite from Day 1)
Duration: 1 Years
Interview Mode: Video Interview Accepted
We are seeking a Senior Machine Learning Engineer with extensive experience in building deploying and managing ML models using AWS SageMaker. The ideal candidate will play a critical role in designing and implementing scalable machine learning solutions in a cloud-native environment. This is a long-term opportunity with one of our top clients in the financial/insurance domain.
Key Responsibilities:Develop deploy and monitor machine learning models using Amazon SageMaker.
Collaborate with data scientists data engineers and business stakeholders to understand business problems and deliver ML-based solutions.
Design and implement end-to-end ML pipelines including data preprocessing model training validation and deployment.
Optimize performance of existing models and improve accuracy and efficiency.
Automate ML workflows and ensure best practices in MLOps.
Maintain model versioning experiment tracking and production deployment monitoring.
Work in an Agile environment and contribute to sprint planning code reviews and stand-ups.
6 years of experience in Machine Learning / Data Science / AI Engineering roles.
Hands-on expertise with AWS SageMaker (mandatory).
Strong programming skills in Python and experience with ML libraries like TensorFlow PyTorch scikit-learn etc.
Proficiency in deploying and maintaining ML models in production environments.
Strong understanding of AWS ecosystem and services related to ML (e.g. Lambda S3 EC2 Step Functions etc.).
Experience with data wrangling using Pandas NumPy and large-scale data handling.
Familiarity with CI/CD pipelines for ML and tools like MLflow Kubeflow or Airflow is a plus.
Excellent problem-solving and communication skills.
Full-time