Data Architect ( AI/Ml or Gen AI models)

10 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Contractual

Job Description

Key Responsibilities

As a Data Architect with Generative AI expertise, you will:

  • Design and implement

     robust data architectures that support AI and machine learning (ML) workloads, including Generative AI applications.
  • Develop and optimize 

    data pipelines

     for training, validating, and deploying AI models efficiently and securely.
  • Integrate AI frameworks

     into data platforms, ensuring scalability, low latency, and high throughput.
  • Collaborate

     with data scientists, AI engineers, and stakeholders to align data strategies with business goals.
  • Lead initiatives to ensure 

    data governance

    , security, and compliance standards (e.g., GDPR, CCPA) are met in AI-driven environments.
  • Prototype and implement

     architectures that utilize generative models (e.g., GPT, Stable Diffusion) to enhance business processes.
  • Stay up to date with the latest trends in Generative AI, data engineering, and cloud technologies to recommend and integrate innovations.

Required Qualifications

We’re looking for someone with:

  • bachelor’s degree

     in Computer Science, Data Engineering, or a related field (master’s preferred).
  • 10+ years

     of experience in data architecture, with a focus on AI/ML-enabled systems.
  • Hands-on experience with 

    Generative AI models

     (e.g., OpenAI GPT, BERT, or similar), including fine-tuning and deployment.
  • Proficiency in 

    data engineering tools and frameworks

    , such as Apache Spark, Hadoop, and Kafka.
  • Deep knowledge of 

    database systems

     (SQL, NoSQL) and 

    cloud platforms

     (AWS, Azure, GCP), including their AI/ML services (e.g., AWS Sagemaker, Azure ML, GCP Vertex AI).
  • Strong understanding of 

    data governance

    MLOps

    , and 

    AI model lifecycle management

    .
  • Experience with programming languages such as 

    Python

     or 

    R

     and frameworks like 

    TensorFlow

     or 

    PyTorch

    .
  • Excellent problem-solving and 

    communication skills

    , with a demonstrated ability to lead cross-functional teams.

Preferred Skills

  • Familiarity with 

    LLM fine-tuning

    prompt engineering

    , and 

    embedding models

    .
  • Strong domain expertise in Life Science Industry
  • Experience integrating generative AI solutions into production-level applications.
  • Knowledge of 

    vector databases

     (e.g., Pinecone, Weaviate) for storing and retrieving embeddings.
  • Expertise in 

    APIs for AI models

    , such as OpenAI API or Hugging Face Transformers.


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