CTO - AI/ML Engineer

5 - 10 years

25 - 30 Lacs

Posted:1 week ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Introduction:

Key Responsibilities:

  • Design, develop, and maintain robust backend systems integrating advanced AI and ML capabilities.
  • Implement and optimize LangChain for efficient language model chaining and application.
  • Manage and manipulate data using vector databases to enhance model performance and scalability.
  • Develop and deploy solutions based on SLM, LLMs, RAG, and Graph RAG to solve complex problems and improve user interactions.
  • Collaborate with cross-functional teams to define clear specifications, deliverables, and timelines.
  • Stay abreast of industry trends and advancements in AI and ML technologies, applying this knowledge to drive continuous improvement in our solutions.
  • Write clean, manageable code and maintain proper documentation.
  • Conduct code reviews, and mentor junior engineers, promoting best practices in software development and AI integration.
  • Ensure the performance, quality, and responsiveness of applications
  • Qualifications:

    • Bachelors or Masters degree in Computer Science, or a related field.
    • Proven experience (5 years) as a Software Engineer with a focus on backend development.
    • Expertise in Python programming and familiarity with frameworks and libraries relevant to AI and ML.
    • Strong experience with Building solutions with LangChain, vector databases, and technologies such as MongoDB, Qdrant and Pinecone.
  • Profound knowledge of SLM, LLMs, RAG, Graph RAG, and other Generative AI concepts.
  • Excellent skills in software design, data structures, and algorithms.
  • Experience with software development tools including version control systems (e.g., Git), continuous integration/continuous deployment (CI/CD) pipelines.
  • Strong analytical and problem-solving skills.
  • Excellent communication and teamwork skills.

Preferred Skills:

  • Experience with cloud platforms (AWS, Google Cloud, Azure) and understanding of scalable architecture.
  • Familiarity with containerization and orchestration technologies (Docker, Kubernetes).

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