2 - 5 years

1 - 6 Lacs

Posted:3 hours ago| Platform: GlassDoor logo

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On-site

Job Type

Full Time

Job Description

JD:

We’re looking for a passionate AI Engineer to join our growing team at GWC Data.AI. In this role, you will work closely with data scientists, software engineers, and product teams to build, deploy, and scale cutting-edge AI solutions. You'll work hands-on with technologies like Deep Learning, Retrieval-Augmented Generation (RAG), LangChain, and Python, solving real-world challenges across diverse domains.

Key Responsibilities:

  • Design, develop, and deploy scalable machine learning and deep learning models.
  • Build and optimize RAG pipelines and LangChain-based LLM applications.
  • Collaborate with product and tech teams to integrate AI models into real-world applications.
  • Process and analyze large datasets to derive actionable insights.
  • Maintain and improve end-to-end AI pipelines using TensorFlow, PyTorch, and Scikit-learn.
  • Conduct research to stay up-to-date with the latest developments in AI, NLP, and Generative AI.
  • Evaluate model performance, implement retraining strategies, and monitor outputs for quality.

Required Skills & Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, AI, or related field.
  • 2–5 years of hands-on experience in AI/ML engineering.
  • Strong coding skills in Python and familiarity with AI libraries like TensorFlow, PyTorch, Scikit-learn.
  • Experience with Retrieval-Augmented Generation (RAG) and LangChain frameworks.
  • Solid understanding of NLP, transformers, and vector databases (e.g., FAISS, Pinecone, Weaviate).
  • Proficiency in Pandas, NumPy, and SQL for data handling.
  • Experience with cloud platforms (AWS, GCP, or Azure) and version control tools like Git.

Job Type: Full-time

Pay: ₹15,773.05 - ₹52,938.83 per month

Schedule:

  • Day shift

Experience:

  • AI : 3 years (Preferred)
  • Python: 3 years (Preferred)
  • LANG CHAIN: 1 year (Preferred)
  • Deep learning: 2 years (Preferred)
  • RAG: 2 years (Preferred)

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