AI Architect Specialist

2 weeks ago

Kottayam, Kerala, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Job Title: Artificial Intelligence Strategist

We are seeking a skilled Artificial Intelligence Strategist to design and develop cutting-edge AI applications.

The successful candidate will have expertise in designing and developing complex AI systems using Python and development tools such as LangChain, LlamaIndex, LangFlow, Langgraph, LangSmith, Flowise.

Key Responsibilities:
  1. Design and develop AI applications using Python and development tools.
  2. Develop expertise in RAG techniques, vector databases (Pinecone, Weaviate, Qdrant), knowledge graphs, FastAPI, Streamlit, Gradio, and other additional technologies.
Requirements:
  1. 8-15 years of experience in AI application development.
  2. Proficiency in programming languages such as Python, data engineering, and OSS LLMs (Llama2, Mixtral, GPT-Neo, GPT-J).
  3. Experience with tokenization and frameworks like Tokenizers (SentencePiece, Hugging Face Tokenizers) and fine-tuning frameworks (Hugging Face Transformers, PyTorch Lightning).
  4. Familiarity with datasets such as HuggingFace Datasets and TensorFlow Datasets.
  5. Strong understanding of LLMOps proficiency, including infrastructure and CI/CD tools like DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions.
  6. Experience with monitoring and management tools like Ray, SeldonCore, MLFlow, MLServer, Triton, BentoML, Prometheus, Grafana.
  7. Ability to work with data processing and management tools like Apache Spark, Apache Kafka, AWS S3, Azure Data Lake Storage (ADLS), Delta Lake.
  8. Experience with workflow automation tools like Apache Airflow, dbt, Apache NiFi, Fivetran, Airbyte, Great Expectations.
  9. Knowledge of data catalogs like Amundsen, Collibra, Alation.
  10. Understanding of AI-ready cybersecurity knowledge, including threat modeling and security, AI security monitoring tools, prompt injection prevention libraries, and adversarial example detection libraries.
  11. Experience with gen AI guardrails and ethics, including AI ethics frameworks and tools, bias detection and mitigation tools, fairness metrics libraries, privacy-preserving machine learning libraries, robustness and security tools, model interpretability libraries, and AI governance frameworks and tools.
  12. Ability to monitor and evaluate the performance of AI applications using metrics like Bleu, Rouge, Perplexity, BERT-Score etc.

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