Senior AI/ML Engineer

1 week ago


India Intechive Systems Full time

We are seeking dedicated AI/ML Senior Developers ranging in 4-9 years experience and a strong interest in Enterprise Use cases of Generative AI leveraging Public and Open Source Large Language Models (LLMs) and other Generative AI technology components. The role is challenging to work on the newest Gen AI stack for implementation in Enterprises.


Responsibilities

  • Develop solutions using AI tools / frameworks utilizing technologies such as Azure OpenAI, LLama3, and other open source Large Language Models (LLMs).
  • Ability to fine-tune LLMs with specific datasets for enhanced performance tailored to distinct use cases.
  • Deepen your understanding of the data preparation process, the subtleties of the fine-tuning procedure, and the challenges it presents.
  • Engage with Retrieval-Augmented Generation (RAG) to blend retrieval-based methods with generative models, improving outcomes in areas like question answering and document summarization.
  • Build Agentic Workflows to enhance the capabilities of the AI Solution.
  • Drive adoption of AI solutions within the Enterprise.
  • Should not hesitate in learning and building innovative solutions in newer technology stacks.


Qualifications

  • Advanced proficiency in Python, JavaScript, SQL, and related languages/tools used in building AI solutions
  • Familiarity with deep learning and machine learning algorithms and the use of popular AI/ML frameworks
  • Comfortable with deployment to both on-premise and cloud infrastructure including Kubernetes, Serverless platforms.
  • Knowledge of Git, CI/CD processes and implementing automated testing
  • Comfortable with both Python and JavaScript implementations of LangChain / LlamaIndex.
  • Competency in implementing LangChain/LangGraph Agents.
  • Proficiency in Vector Databases Weaviate, QDrant or similar vector databases.
  • Proficiency in Graph Databases Neo4j.
  • Open to experiment with different technology stacks to achieve optimal solution for clients.
  • Expertise in Prompt Engineering: Create precise prompts to extract targeted responses from LLMs, considering the nuances of each model.
  • Mastery in Contextual Prompting: Ensure the preservation of conversational context to facilitate coherent and meaningful dialogue with LLMs.
  • Strategies for Addressing LLM Hallucination: Recognize the issues posed by LLM hallucinations, and learn to implement guardrails.
  • Knowledge of building backend APIs for AI solutions to be integrated with frontend frameworks.
  • Experience working with large data sets and writing efficient code capable of processing large data streams at speed




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