Manager, AI Research
Tasks
- Apply reinforcement learning with human feedback
- Benchmark model performance
- Build experimental pipelines
- Containerize ML workflows
- Create embedding based retrieval systems
- Design agent workflows
- Develop agentic AI solutions
- Develop model optimization algorithms
- Distill models
- Ensure model reproducibility
- Fine-tune models
- Implement MLOps experiment tracking
- Implement retrieval-augmented generation
- Prototype generative AI LLM systems
- Quantize models
- Research AI/ML models
- Set up CI CD for models
- Train and evaluate models
- Transition prototypes into production
- Use vector databases
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic Workflows | Autonomous Agents | C plus plus | CI/CD | Deep learning | Docker | Embedding Models | Experiment tracking | Fine Tuning | Generative AI | Hugging Face | Human Feedback | Java | Knowledge Distillation | Kubernetes | Language Models | Large Language Models | MLOps | Machine Learning | Model Benchmarking | Model Quantization | Multimodal Models | PyTorch | Python | Reinforcement Learning | Reproducibility | Retrieval systems | Retrieval-Augmented Generation | TensorFlow | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Research Manager | AI Researcher | Manager | Research Manager | Researcher
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