Sr AI Engineer

3 - 6 years

20 - 30 Lacs

Posted:1 day ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Job Title: AI/ML Engineer

Experience Level

Job Summary

AI/ML Engineer

Python

Roles & Responsibilities

  1. Model Development & Training

    • Design, train, and fine-tune

      AI/ML models

      , especially

      Generative AI

      and

      Large Language Models (LLMs)

      , to address specific use cases.
    • Build conversational AI solutions and chatbots using frameworks such as

      LangChain

      ,

      RAG (Retrieval-Augmented Generation)

      , and

      Chain-of-Thought (COT) prompting

      .
    • Apply advanced techniques, including

      embeddings

      , fine-tuning, and custom prompting strategies.
    • Incorporate

      REACT (Retrieve, Extract, Adapt, Construct, Think)

      methods to enhance model capabilities.
    • Develop scalable AI solutions to integrate seamlessly into production environments.
  2. Data Handling

    • Manage

      large-scale datasets

      for AI/ML applications, ensuring data quality, transformation, and normalization.
    • Conduct

      data analysis, preprocessing, and munging

      to extract valuable insights.
    • Implement scalable data engineering workflows for model development and production.
  3. Cloud AI/ML Deployment

    • Deploy, manage, and optimize AI models on

      Google Cloud Platform (GCP)

      (or other cloud platforms like AWS/Azure).
    • Leverage GCP services such as Vertex AI, BigQuery, Cloud Functions, and Dataflow for AI workflows.
  4. Collaboration & Solutioning

    • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers, to deliver AI-driven solutions.
    • Integrate models with client-facing applications, ensuring end-to-end implementation.
    • Support scalable development through

      Docker

      for containerization (a plus).
  5. Continuous Improvement

    • Stay updated with the latest advancements in AI, ML, and Generative AI frameworks, tools, and methodologies.
    • Proactively learn new technologies and apply them to improve processes and solutions.
  6. Web Scraping (Optional but Preferred)

    • Implement

      web scraping

      solutions to gather data from unstructured sources for model training and validation
    • .

Required Skills & Qualifications

  • 3-6 years

    of experience in AI/ML model development, training, and fine-tuning.
  • Strong programming skills in

    Python

    and

    SQL

    .
  • Hands-on experience with

    Generative AI

    ,

    LLMs

    , and

    NLP techniques

    .
  • Experience working with

    LangChain

    ,

    RAG frameworks

    , and advanced prompting strategies.
  • Proficiency in Chain-of-Thought (

    CoT

    ) prompting, Model Context Protocol

    (MCP)

    , and Agent-to-Agent (

    A2A

    ) orchestration
  • Proficiency in

    embeddings

    and fine-tuning models for specific tasks.
  • Strong understanding of

    machine learning algorithms

    and statistical analysis.
  • Experience working with

    large datasets

    and scalable data processing workflows.
  • Hands-on experience with

    GCP (Vertex AI, BigQuery)

    or other cloud platforms (AWS/Azure).
  • Knowledge of

    Docker

    for deployment and containerization.
  • Solid skills in

    data cleaning, transformation, and normalization

    for data integrity.

Preferred Skills

  • Familiarity with

    Reinforcement Learning from Human Feedback (RLHF)

    .
  • Understanding of

    COT (Chain-of-Thought) prompting

    .
  • Proficiency in

    REACT (Retrieve, Extract, Adapt, Construct, Think)

    frameworks.
  • Experience in

    web scraping

    techniques.

Key Attributes

  • Strong analytical and problem-solving abilities.
  • Ability to work independently as well as collaboratively in a team environment.
  • Excellent communication skills to interact with stakeholders and cross-functional teams.
  • Proactive attitude to learn and adopt new AI technologies and frameworks.

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