Senior Artificial Intelligence/Machine Learning Engineer
Tasks
- Automate Kubernetes and distributed computing environments
- Build automated AI and analytics lifecycle platform services
- Conduct technical design reviews and code reviews
- Design self service platform automation capabilities
- Develop infrastructure as code solutions
- Drive observability automated remediation and reliability engineering
- Enable agentic AI applications and event driven workflows
- Implement CI/CD pipelines and release management
- Lead enterprise GenAI automation initiatives
- Provide engineering mentorship and technical leadership
Perks/Benefits
- Company-paid certifications
- Financial consultations
- Language courses
- Legal consultations
- Medical insurance
- Mental health support
- Paid training
- Udemy access
Skills/Tech-stack
API Integrations | Agentic AI | Alerting | Atlassian Bamboo | Atlassian Bitbucket | Atlassian Confluence | Atlassian Jira | CI/CD | Containers | Data Governance | Data Lineage | Data Quality | DevOps | DevSecOps | Distributed Computing | Event Streaming | Generative AI | Infrastructure as Code | Kafka | Kubernetes | Language Models | Large Language Models | Logging | MCP | Machine Learning | Metadata Management | Microservices | Model Management | Monitoring | Observability | Python | RAG | Semantic layer | Serverless | Terraform | Tracing | YARN | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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