Junior AI/ML Engineer
Tasks
- Apply scaling strategies
- Build and test microservices
- Build data pipelines
- Build model training workflows
- Collaborate with agile teams
- Collect system telemetry
- Configure CI/CD pipelines
- Configure and monitor Kafka topics
- Deploy models to production workflows
- Develop Event Driven services
- Document compliance with reference architectures
- Evaluate models
- Extract features
- Implement security scanning
- Integrate with Apache Kafka
- Manage Kubernetes deployments
- Manage build test and artifact workflows
- Manage training evaluation deployment pipelines
- Participate in code reviews
- Perform Kubernetes health checks
- Prepare training data
- Run AI ML experiments
- Set up automated tests
- Support infrastructure automation
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agile | Apache Airflow | Apache Kafka | Automated testing | Azure | C++ | CI/CD | Cloud platform | Confluence | Containerization | Data Pipelines | DevSecOps | Docker | Feature Engineering | Flink | Google Cloud | Google Cloud Platform | Helm | Infrastructure automation | Ingress | Java | Jira | Kafka Streams | Kanban | Kubernetes | MLOps | Machine Learning | Model Deployment | Model Monitoring | Model Training | Prefect | PyTorch | Python | SBOM | Scrum | Security Scanning | Service Mesh | Spark Streaming | TensorFlow | Terraform | Zero Trust
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