AI | ML Engineering Consultant
Tasks
- Build scalable data and model pipelines
- Deploy agentic frameworks into production
- Establish LLMOps best practices
- Lead end to end development and deployment of large language models
- Lead end to end development and deployment of machine learning models
- Manage model lifecycle
- Monitor models and implement guardrails
- Own experimentation strategy
- Partner with cross-functional teams
- Provide technical leadership and mentoring
- Run experiments and assess feasibility
Perks/Benefits
Skills/Tech-stack
AWS | Agentic Frameworks | Autogen | Azure | Cloud platform | Docker | Experimental Design | Fine Tuning | Generative AI | Google Cloud | Google Cloud Platform | LLM architectures | LLMOps | Langchain | Language Models | Large Language Models | Lifecycle Management | Llamaindex | MLOps | Machine Learning | Model Lifecycle | Model Lifecycle Management | Model Monitoring | Python | RAG | RLHF | Reinforcement Learning
Education
Roles
AI | AI Engineer | Consultant | Data Science | Data Science Consultant | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
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