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Generative AI Engineer - Artificial Intelligence / Machine Learning

Generative AI Engineer - Artificial Intelligence / Machine Learning

MEEDEN LABS PRIVATE LIMITEDChennai
30+ days ago
Job description

Role Overview :

We are seeking highly skilled Generative AI Engineers to join our AI innovation team. The ideal candidate will have hands-on experience in designing, developing, and deploying AI / ML solutions with expertise in cloud platforms (Azure, GCP, or AWS). Candidates with deeper experience in LLMs, RAG, and advanced AI architectures will be considered for senior-level roles.

Key Responsibilities :

  • Design, develop, and implement AI-driven applications leveraging Generative AI, LLMs, and related frameworks.
  • Collaborate with cross-functional teams to integrate AI solutions into enterprise systems and products.
  • Deploy and scale AI / ML models on cloud platforms (Azure, GCP, or AWS) ensuring performance, scalability, and security.
  • Research and experiment with Retrieval-Augmented Generation (RAG) techniques to improve contextual accuracy in AI outputs.
  • Fine-tune and optimize Large Language Models (LLMs) for domain-specific use cases.
  • Stay up-to-date with the latest advancements in Generative AI, ML Ops, and cloud-native AI services.
  • Provide mentorship and technical guidance to junior engineers (for senior-level roles).

Required Skills & Experience :

For 3 - 5 Years Experience :

  • Strong background in Artificial Intelligence / Machine Learning (NLP, Generative AI).
  • Hands-on experience with Azure AI Services / GCP Vertex AI / AWS Bedrock (any 2 cloud platforms preferred).
  • Proficiency in Python, ML frameworks (TensorFlow, PyTorch, Hugging Face).
  • Knowledge of APIs, cloud deployment, and model lifecycle management.
  • For 6 - 7 Years Experience (Senior Level) :

  • Proven expertise in LLMs (GPT, LLaMA, etc.) and RAG pipelines.
  • Strong understanding of vector databases (Pinecone, Weaviate, FAISS, etc.).
  • Experience in fine-tuning and optimizing large-scale models for production.
  • Ability to design and implement scalable AI architectures in multi-cloud environments.
  • Experience in leading AI projects, mentoring teams, and client interaction.
  • (ref : hirist.tech)

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