Lead Machine Learning Engineer
Tasks
- Architect AI systems and chatbots
- Build RAG systems
- Collaborate with scientists to fine tune and deploy LLMs
- Deploy LLM services as scalable microservices
- Establish prompt engineering best practices
- Implement reinforcement learning frameworks
- Integrate AI features into platform
- Manage data for transparency and governance
- Manage dialogue and workflow execution
- Monitor and evaluate models across lifecycle
- Orchestrate multi-agent systems
Perks/Benefits
- Dental insurance
- Disability insurance
- Holidays
- Life insurance
- Medical insurance
- Paid time off
- Retirement plan
- Stock options
- Vision insurance
Skills/Tech-stack
Agent Orchestration | Anthropic API | Automated testing | Azure | CI/CD | ChromaDB | Deep learning | Docker | Fine Tuning | Git | Kubernetes | LLM Agents | Language Models | Language Processing | Large Language Models | Llama | LoRA | Machine Learning | Microservices | Mistral | Model Evaluation | Monitoring | Multi-Agent | Multi-agent orchestration | Natural Language | Natural Language Processing | Open Source | Open-source Models | OpenAI API | Pinecone | Prompt engineering | PyTorch | Python | QLoRA | Reinforcement Learning | Retrieval-Augmented Generation | TensorFlow | Vector Databases | Weaviate
Education
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