GenAI Engineer
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Job Summary (List Format):
- Design fine-tune and deploy advanced AI-driven text applications using Large Language Models (LLMs) and NLP techniques
- Collaborate with business units to identify and support impactful AI use cases
- Develop LLM-based applications using models like GPT LLaMA and BERT
- Optimize LLMs for various tasks such as sentiment analysis summarization translation and conversational AI
- Work with tokenization embeddings and vector databases (e.g. FAISS Pinecone) for semantic search and retrieval
- Integrate AI models into production systems in partnership with product and engineering teams
- Apply ML Ops best practices for scalable model deployment versioning monitoring and CI/CD
- Ensure compliance with data privacy regulations ethical AI standards and GDPR
- Present findings insights and recommendations to executive stakeholders through high-quality deliverables
- Leverage experience with NLP libraries (Hugging Face Transformers spaCy NLTK OpenAI API) and transformer architectures
- Utilize model optimization techniques (quantization distillation) and manage AI workflows using ML Ops tools
- Work with cloud platforms (AWS Azure GCP) and containerization technologies (Docker Kubernetes)
- Demonstrate strong problem-solving skills and the ability to work in cross-functional teams
- Successfully deploy at least one LLM-based application to production
- Design fine-tune and deploy advanced AI-driven text applications using Large Language Models (LLMs) and NLP techniques
- Collaborate with business units to identify and support impactful AI use cases
- Develop LLM-based applications using models like GPT LLaMA and BERT
- Optimize LLMs for various tasks such as sentiment analysis summarization translation and conversational AI
- Work with tokenization embeddings and vector databases (e.g. FAISS Pinecone) for semantic search and retrieval
- Integrate AI models into production systems in partnership with product and engineering teams
- Apply ML Ops best practices for scalable model deployment versioning monitoring and CI/CD
- Ensure compliance with data privacy regulations ethical AI standards and GDPR
- Present findings insights and recommendations to executive stakeholders through high-quality deliverables
- Leverage experience with NLP libraries (Hugging Face Transformers spaCy NLTK OpenAI API) and transformer architectures
- Utilize model optimization techniques (quantization distillation) and manage AI workflows using ML Ops tools
- Work with cloud platforms (AWS Azure GCP) and containerization technologies (Docker Kubernetes)
- Demonstrate strong problem-solving skills and the ability to work in cross-functional teams
- Successfully deploy at least one LLM-based application to production
Key Skills
- ASP.NET
- Health Education
- Fashion Designing
- Fiber
- Investigation
