Senior ML Engineer (AI Research/ Portability)
Tasks
- Apply reinforcement learning and skill generation
- Build AI agent architectures
- Build integration layers and testing infrastructure
- Build retrieval systems
- Collaborate with research engineering security and product teams
- Create evaluation frameworks and benchmarks
- Define agent schemas interfaces and standards
- Design machine learning models
- Develop portable abstractions across models providers and protocols
- Develop research software and APIs
- Develop scalable memory and context management
- Evaluate machine learning models
- Implement agent interoperability solutions
- Implement model routing systems
- Implement tool execution and multi agent workflows
- Optimize quality cost latency
- Produce technical documentation and research publications
- Research model distillation and knowledge transfer
- Train machine learning models
Perks/Benefits
- Career growth opportunities
- Collaborative culture
- Continuous learning support
- Flexible working environment
- Inclusive workplace focused on innovation trust and meaningful impact
- International teams
- Ownership and autonomy
Skills/Tech-stack
AI Agents | APIs | Artificial Intelligence | CI/CD | Data schemas | Distributed Systems | Evaluation Frameworks | Knowledge Distillation | Knowledge graphs | Language Models | Large Language Models | Machine Learning | Memory Architectures | Model routing | Observability | Privacy | Protocols | Provenance | Python | Reinforcement Learning | Retrieval systems | Security | Testing | Vector Databases | Version control
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