AI Systems Developer

2 days ago

Coimbatore, Tamil Nadu, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Artificial Intelligence Engineer

We are seeking a highly skilled Artificial Intelligence Engineer to join our team. This is an exciting opportunity to work on cutting-edge AI projects and contribute to the development of innovative solutions.

  • Design and implement robust NLP pipelines for classification, named entity recognition (NER), summarization, sentiment analysis, and question-answering tasks using various machine learning models and tools such as SpaCy, NLTK, and Hugging Face Transformers.
  • Fine-tune and optimize pre-trained language models like BERT, T5, and GPT-style variants using transfer learning and hyperparameter tuning techniques.
  • Integrate large language model APIs from providers like OpenAI, Anthropic/Claude, Cohere, and Hugging Face into real-time applications and microservices, ensuring seamless interaction with product teams.
  • Develop and evaluate prompt strategies for few-shot or zero-shot approaches, leveraging vector databases like FAISS, Weaviate, and Pinecone for efficient information retrieval.
  • Deploy model endpoints using Flask, FastAPI, or Streamlit, containerize them with Docker, and collaborate on cloud deployment with DevOps engineers.
  • Monitor model performance, data drift, and user feedback; iterate based on metrics and qualitative signals to maintain high-quality AI systems.
Requirements:
  • Strong Python skills with experience working with popular libraries like SpaCy, Transformers, and NLTK.
  • Hands-on experience fine-tuning/training transformer models like BERT, T5, and GPT variants using Hugging Face Transformers.
  • Experience integrating LLM APIs and working with prompt engineering techniques.
  • Familiarity with concepts like embeddings, attention, tokenization, and vector similarity (cosine) is essential for this role.
  • Experience working with vector databases like FAISS, Weaviate, or Pinecone for efficient information retrieval.
  • Comfortable with containerization using Docker, Git version control, and REST API development using Flask or FastAPI.
  • Practical knowledge of evaluation metrics like BLEU, ROUGE, perplexity, and cosine similarity is necessary for assessing AI system performance.
Sr. Roles:
  • Track record of shipping multiple production LLM/NLP systems end-to-end, demonstrating expertise in system design and architecture.
  • Strong system design skills to handle latency and cost tradeoffs, multi-tenant inference, and scalability requirements.
  • Mentoring/leadership experience and ownership of ML lifecycle (MLOps) processes are essential for Sr. Roles.
Preferred / Nice-to-Have Skills:
  • Experience with LLMOps tooling like LangChain, LlamaIndex, PromptLayer, or similar platforms.
  • RAG workflows and building retrieval pipelines at scale using efficient algorithms and architectures.
  • Experience in cloud deployment on AWS, GCP, or Azure platforms.
  • Contributions to open-source projects or research publications in the field of natural language processing and machine learning.

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