Senior ML Engineer (AI Research/ Portability)
Tasks
- Build AI agent architectures
- Build memory context management systems
- Build model routing systems
- Build multi-agent workflows
- Build retrieval systems
- Collaborate with research engineering security product teams
- Create benchmarks
- Define agent schemas and interfaces
- Design machine learning models
- Develop evaluation frameworks
- Develop research software APIs and integration layers
- Evaluate machine learning models
- Implement machine learning models
- Implement tool execution
- Optimize quality cost latency
- Prototype agent interoperability
- Set up testing infrastructure
- Train machine learning models
- Write technical documentation and publish findings
Perks/Benefits
- Career growth opportunities
- Collaborative international teams
- Continuous learning support
- Flexible working environment
- Inclusive workplace
- Ownership and autonomy
Skills/Tech-stack
APIs | CI/CD | Distillation | Distributed Systems | Evaluation Frameworks | Generalization | Interoperability | Knowledge graphs | Language Models | Large Language Models | Machine Learning | Mixture of Experts | Model routing | Observability | Preference Learning | Privacy | Provenance | Python | Reinforcement Learning | Retrieval systems | Reward Modeling | Security | Statistical methodology | Testing | Uncertainty Estimation | Vector Databases | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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