ML Engineer
Tasks
- Build API-driven backend services
- Collaborate with data scientists and engineers
- Design and build end-to-end AI systems
- Develop data and model pipelines
- Ensure scalable reliable secure performant systems
- Implement agent-based workflows
- Integrate LLMs
- Integrate machine learning models
- Maintain system documentation and knowledge transfer
- Operationalize model outputs in production systems
- Orchestrate multi step processes
- Test monitor and optimize system performance
- Translate ambiguous problems into structured requirements
- Translate business requirements into technical architectures
Perks/Benefits
Skills/Tech-stack
Agentic Workflows | Application Programming | Application Programming Interfaces | Data Pipelines | Docker | Java | Kubernetes | Language Models | Large Language Models | Machine Learning | Model Pipelines | Monitoring | Orchestration | Performance optimization | Programming interfaces | Python | REST | SQL | Scalability | Security | System Architecture | Testing
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Science in Computer Science | Bachelor of Science in Data Science | Bachelor of Science in Machine Learning
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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