AI Engineer

4 days ago

Pune, Maharashtra, India beBeeGenerative Full time US$ 1,22,400 - US$ 1,74,600

Job Title: AI Engineer - Generative Models

 

We are seeking an experienced AI Engineer - Generative Models to join our team. As a key member of our AI Team, you will be responsible for designing, developing, and deploying state-of-the-art machine learning models with a focus on Generative AI.

 

Key Responsibilities:

  • Design, develop, and deploy scalable ML solutions using LLMs and RAG architecture.
  • Implement and optimize prompt engineering, embeddings, vector databases, and retrieval mechanisms.
  • Develop APIs and services to integrate AI solutions into production systems.
  • Collaborate with data engineers, product managers, and other stakeholders to define technical requirements.
  • Continuously evaluate and improve model performance and accuracy.
  • Stay updated with the latest research and developments in GenAI, NLP, and ML.
  • Contribute to technical documentation, code reviews, and best practices.
  • Ensure all AI solutions comply with ethical and data privacy standards.

 

Required Skills and Qualifications:

  • Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
  • Strong programming skills in Python, including use of libraries like TensorFlow, PyTorch, Hugging Face Transformers, LangChain, etc.
  • Experience with LLMs (GPT, LLaMA, Claude, etc.) and RAG frameworks.
  • Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate).
  • Solid understanding of NLP, embeddings, tokenization, and attention mechanisms.
  • Familiarity with APIs, RESTful services, and cloud deployment (AWS/GCP/Azure).
  • Strong foundation in data structures, algorithms, and ML workflows.

 

Benefits:

  • Opportunity to work on cutting-edge AI projects.
  • Collaborative and dynamic work environment.
  • Professional development and growth opportunities.

 

Success Measures (KPIs):

  • Time to deploy new ML/GenAI features.
  • Accuracy and performance of deployed models.
  • User engagement and satisfaction with AI features.
  • Uptime and reliability of AI services.
  • Contribution to AI/ML research or innovation within the team.
  • Reusability and scalability of AI code and systems.

 

Competency Framework Alignment:

  • Technical Expertise: Mastery in Python, ML frameworks, GenAI, and RAG.
  • Innovation: Drives AI innovation and creative problem-solving.
  • Collaboration: Works effectively in multi-disciplinary teams.
  • Execution Excellence: Delivers high-quality, scalable AI solutions.
  • Customer Focus: Builds AI features that enhance user experience.
  • Ethical Responsibility: Ensures responsible AI practices and data governance.

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