Senior AI ML Engineer

18 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

Hello There!


Casepoint Pvt. Ltd., Surat..!


About Company:


Casepoint provides full eDiscovery capabilities through a powerful, secure, cloud-based platform. We are repeatedly chosen by leading law firms and multinational corporations for their largest matters. On an upward trajectory for almost a decade, Casepoint is looking to expand its team globally. Team cooperation, “work hard, play hard” attitude, open communication, and kindness mark Casepoint’s culture.



Senior


Key Responsibilities:


  • Design, develop, and deploy 

    machine learning and AI models

    , with a strong focus on 

    Generative AI

     applications.
  • Implement 

    model fine-tuning

    Retrieval Augmented Generation (RAG)

    , and 

    prompt engineering

     techniques.
  • Integrate and optimize 

    open-source and commercial AI models

     (e.g., 

    Hugging Face

    OpenAI

    Claude

    Gemini

    LlamaIndex

    LangChain

    ).
  • Build and manage 

    data pipelines

     for ingestion, transformation, and model training.
  • Enhance 

    data collection and preprocessing

     methods to improve model accuracy and robustness.
  • Work with 

    vector databases

     and embeddings to enable semantic search and intelligent retrieval.
  • Collaborate with cross-functional teams to integrate ML models into production systems and monitor performance.
  • Develop and maintain 

    automated model evaluation, retraining, and anomaly detection systems

    .
  • Conduct experiments, evaluate model results, and present insights clearly to stakeholders.


Required Skills:


  • Strong programming skills in 

    Python

     and libraries such as 

    NumPy

    Pandas

    Scikit-learn

    , and 

    PyTorch/TensorFlow

    .
  • Hands-on experience with 

    Generative AI frameworks

    model fine-tuning

    , and 

    RAG pipelines

    .
  • Experience integrating 

    LLMs

     via APIs or frameworks (

    LangChain

    LlamaIndex

    , etc.).
  • Familiarity with 

    vector storage solutions

     (e.g., FAISS, Pinecone, Chroma).
  • Sound understanding of 

    data preprocessing

    feature engineering

    , and 

    model evaluation

     techniques.
  • Exposure to 

    cloud environments

     (AWS, GCP, or Azure) and 

    MLOps

     tools is a plus.


Copensation & Culture:


great culture builds great products


Experience:

Location:

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Casepoint

Legal Technology

Arlington

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