Proactively assess and monitor your cloud environments based on operational excellence, security, reliability, performance efficiency and cost optimisation. CloudPlexo provides both developers and management with the insights needed to run an efficient, lean and reliable cloud environment. CloudPlexo Cloud Management Platform (CCMP) is a Software-as-a-Service (SaaS) cloud management solution. We provide a software platform for businesses to acquire a full view of their cloud health, cost and operations from multiple cloud environments in one platform.
Key Responsibilities:
- Design, develop, and deploy machine learning models using AWS AI/ML services (SageMaker, Bedrock, Lex, Rekognition, etc.).
- Optimize and fine-tune ML models for performance, scalability, and cost-efficiency.
- Implement MLOps pipelines for automated training, deployment, and monitoring.
- Collaborate with data engineers to build robust data pipelines (Glue, Athena, Redshift, etc.).
- Work with AWS services like Lambda, Step Functions, ECS, and S3 to integrate AI/ML into cloud-native applications.
- Stay updated with the latest advancements in generative AI, LLMs, and deep learning.
- Provide technical guidance to clients and internal teams on AI/ML best practices.
Required Skills and Experience:
- 3+ years of hands-on experience in AI/ML model development and deployment.
- Strong proficiency in Python, TensorFlow, PyTorch, or scikit-learn.
- Experience with AWS AI/ML stack (SageMaker, Bedrock, Claude, Titan, etc.).
- Knowledge of MLOps tools (SageMaker Pipelines, MLflow, Kubeflow).
- Familiarity with big data technologies (Spark, Hadoop, Databricks) is a plus.
- AWS certifications (AWS Certified ML – Specialty) are highly desirable.
- Strong problem-solving skills and ability to work in fast-paced environments.
Method of Application
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