Senior Machine Learning Engineer - AI
Tasks
- Build AI prototypes
- Build evaluation infrastructure
- Define evaluation strategy for agentic systems and LLMs
- Design agentic systems and multi agent orchestration
- Design internal benchmarks and failure mode testing
- Develop AI tools for payments
- Ensure production readiness of AI systems
- Evaluate agentic frameworks and retrieval strategies
- Mentor engineering through code review and research methodology
- Serve as AI technical resource across organization
Perks/Benefits
- N/A
Skills/Tech-stack
Agent Orchestration | Agentic Systems | Context Management | Context engineering | Deployment Pipelines | Ensemble Methods | Failure mode analysis | Fine Tuning | Generative AI | Human-in-the-loop | Inference Optimization | LLM Failure Mode Analysis | Language Models | MLOps | Machine Learning | Memory and context management | Model Deployment | Model deployment pipelines | Multi-Agent | Multi-agent orchestration | Observability | Optimization | Probabilistic Modeling | Production Systems | Python | RLHF | Retrieval-Augmented Generation | State handling | Statistics | Supervised Learning | The Loop | Tool use
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
Cities
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