Senior AI Engineer
Tasks
- Build CI/CD pipelines
- Build REST API integrations
- Create event driven architecture integrations
- Define infrastructure and deployment requirements
- Design large language model based systems
- Develop RAG and agentic applications
- Develop containerized AI components
- Develop model serving and AI service layer
- Ensure code quality and engineering standards
- Implement MLOps workflows
- Integrate AI solutions with enterprise backend systems
- Integrate AI systems into production
- Mentor junior engineers
- Monitor AI systems and optimize performance
- Perform end to end technical design
- Support Docker and Kubernetes deployments
Perks/Benefits
- Employee discounts
- Flexible work arrangement
- Health Fund Support
- Modern office environment
- Private health insurance
- Voluntary Pension Savings Support
Skills/Tech-stack
Agent systems | Agentic Systems | Airflow | BentoML | CI/CD | CUDA | Dask | Data Processing | Deep learning | Distributed data | Distributed data processing | Docker | Event Driven | Event-driven architecture | GPU Computing | Grafana | KServe | Kubeflow | Kubernetes | Language Models | Large Language Models | LoRA | MLOps | MLflow | Machine Learning | Microservices | Multi-Agent | Multi-Agent Systems | PEFT | Prometheus | Python | QLoRA | RAG | REST API | Spark | Triton | VLLM
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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