DBiz.ai - Machine Learning Engineer - AWS & MLOps
20 hours ago
Job Summary :We are seeking a highly skilled and motivated Machine Learning Engineer with a strong foundation in programming and machine learning, hands-on experience with AWS Machine Learning services (especially SageMaker), and a solid understanding of Data Engineering and MLOps practices.You will be responsible for designing, developing, deploying, and maintaining scalable ML solutions in a cloud-native Responsibilities : - Design and implement machine learning models and pipelines using AWS SageMaker and related services.- Develop and maintain robust data pipelines for training and inference workflows.- Collaborate with data scientists, engineers, and product teams to translate business requirements into ML solutions.- Implement MLOps best practices including CI/CD for ML, model versioning, monitoring, and retraining strategies.- Optimize model performance and ensure scalability and reliability in production environments.- Monitor deployed models for drift, performance degradation, and anomalies.- Document processes, architectures, and workflows for reproducibility and Skills & Qualifications : - Strong programming skills in Python and familiarity with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).- Solid understanding of machine learning algorithms, model evaluation, and tuning.- Hands-on experience with AWS ML services, especially SageMaker, S3, Lambda, Step Functions, and CloudWatch.- Experience with data engineering tools (e.g., Apache Airflow, Spark, Glue) and workflow orchestration.- Proficiency in MLOps tools and practices (e.g., MLflow, Kubeflow, CI/CD pipelines, Docker, Kubernetes).- Familiarity with monitoring tools and logging frameworks for ML systems.- Excellent problem-solving and communication Qualifications : - AWS Certification (e.g., AWS Certified Machine Learning Specialty).- Experience with real-time inference and streaming data.- Knowledge of data governance, security, and compliance in ML systems (ref:hirist.tech)
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