Posted:1 day ago|
Platform:
Work from Office
Full Time
Design, develop, and deploy ML models on AWS SageMaker.
Build and maintain scalable ML pipelines (training, testing, deployment, and monitoring).
Collaborate with data engineers to prepare and preprocess large datasets.
Optimize model performance, cost, and scalability in production environments.
Implement MLOps best practices for CI/CD, monitoring, and retraining.
Ensure compliance with data governance, security, and cloud standards.
Qualifications:
Bachelors/Masters in Computer Science, Data Science, or related field.
3+ years of experience in ML model development and deployment.
Strong proficiency in Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Proven expertise with AWS SageMaker and related AWS services (S3, Lambda, Step Functions, ECR, CloudWatch).
Experience with containerization (Docker) and version control (Git).
Familiarity with MLOps practices and ML lifecycle management.
We are seeking a skilled Machine Learning Engineer with hands-on experience in building, deploying, and optimizing ML models using AWS SageMaker. The ideal candidate will work closely with data scientists and engineering teams to operationalize machine learning solutions at scale.
Infiniti Research
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