AI/ML Model Deployment Engineer

13 hours ago

nashik, India beBeeMachineLearning Full time

Job Title: AI/ML Model Deployment Engineer We are seeking an experienced AI/ML Model Deployment Engineer to join our team. The successful candidate will be responsible for deploying, monitoring, and scaling ML models on cloud platforms such as AWS (SageMaker, EKS, Lambda) or GCP (Vertex AI, GKE, Cloud Functions).The ideal candidate will have ~2+ years of experience in working with ML Ops & DS, including building and maintaining CI/CD pipelines for ML workflows using GitHub Actions / Jenkins / cloud-native tools.Containerization and orchestration of workloads will be managed with Docker & Kubernetes, while Terraform/CloudFormation is used to manage infrastructure.Model registries, feature stores, and observability will be implemented using MLflow, Feast, Prometheus/Grafana.Collaboration with data scientists is essential for operationalizing ML models for personalization, recommendations, NLP.Proficiency in Python, ML frameworks (Scikit-learn, TensorFlow, PyTorch), and data pipelines (Airflow, Spark, SQL) is required.Bonus skills include real-time ML serving, A/B testing, or media/recommender systems.Key Responsibilities:Deploying, monitoring, and scaling ML models on cloud platformsBuilding and maintaining CI/CD pipelines for ML workflowsContainerization and orchestration of workloadsImplementing model registries, feature stores, and observabilityCollaborating with data scientists for model operationalizationStaying up-to-date with industry developments and best practicesRequirements:~2+ years of experience in working with ML Ops & DSExperience with cloud platforms (AWS, GCP)Proficiency in Python, ML frameworks, and data pipelinesStrong understanding of containerization and orchestrationKnowledge of model registries, feature stores, and observabilityExcellent collaboration and communication skillsPreferred Skills:Real-time ML servingA/B testingMedia/recommender systemsExperiment design & causal inferenceReal-time ML serving (KFServing, Seldon, Ray Serve)Nice-to-Have Skills:Knowledge of experiment design & causal inferenceExposure to real-time ML serving

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