24 hours ago
Bengaluru, IndiaSenior / Staff+
Responsibilities
- Design, build, and maintain end-to-end ML pipelines for data ingestion, model training, evaluation, deployment, and monitoring.
- Deploy ML models as scalable, highly available, low-latency microservices and APIs.
- Automate infrastructure provisioning and manage CI/CD pipelines for model deployment, versioning, and rollback.
- Integrate ML models into cloud-native architectures using AWS services.
- Improve consistency, observability, and cost efficiency with DevOps and platform teams.
- Implement monitoring and alerting for model performance, data drift, and system health.
- Develop reusable microservices, APIs, and SDKs for ML model integration.
- Maintain standards for code quality, testing, documentation, and software engineering practices.
- Stay current with MLOps, cloud computing, and distributed model serving.
Requirements
- 5–8 years of experience in ML Engineering, Software Engineering, or DevOps focused on machine learning systems.
- Strong Python skills and experience with TensorFlow, PyTorch, or Scikit-learn.
- Strong experience with AWS services including SageMaker, Lambda, ECS/EKS, CloudWatch, S3, and IAM.
- Experience deploying ML models in production using FastAPI, Flask, gRPC, or similar frameworks.
- Hands-on experience with Terraform and Infrastructure as Code.
- Experience with Docker and Kubernetes.
- Understanding of CI/CD pipelines, model registries, and artifact management.
- Knowledge of model monitoring, logging, and observability tools such as Prometheus, Grafana, or Evidently AI.
- Strong software engineering practices, including version control, modular design, automated testing, and code reviews.
- Preferred: bachelor’s or master’s degree in Computer Science, Engineering, or a related field.
- Preferred: experience with AWS CDK, Serverless Framework, or Argo Workflows.
- Preferred: familiarity with API gateways, Kafka, SQS, and event-driven systems.
- Preferred: exposure to A/B testing, canary deployments, and shadow deployments for ML models.
- Experience in AIOps, telecom, or enterprise networking is advantageous.
Tech Stack
Apache KafkaAWSDockerFastAPIFlaskGrafanagRPCKubernetesPrometheusPythonPyTorchscikit-learnTensorFlowTerraform
Categories
About Ericsson
Ericsson is a publicly traded telecommunications vendor that builds mobile network infrastructure (RAN, core, OSS/BSS), cloud platforms, and managed services for communications providers and enterprises. Founded in 1876 and headquartered in Kista, Stockholm, it supplies 5G systems to operators worldwide and owns Vonage, expanding network APIs and enterprise communications offerings.