Posted:1 week ago| Platform: Foundit logo

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Job Type

Full Time

Job Description

  • Key Responsibilities:

  • AI Model Development:

  • Design, develop, and implement

    AI models

    using

    Python

    and machine learning frameworks like

    TensorFlow

    ,

    Keras

    ,

    PyTorch

    , or

    Scikit-Learn

    .
  • Create algorithms and models for a wide range of AI applications, such as

    natural language processing (NLP)

    ,

    image recognition

    ,

    recommendation systems

    , and

    predictive analytics

    .
  • Work with large datasets,

    data preprocessing

    , and

    feature engineering

    to prepare data for training and model validation.
  • Machine Learning and Deep Learning:

  • Apply

    supervised

    and

    unsupervised learning

    techniques to solve problems in areas such as customer segmentation, anomaly detection, and forecasting.
  • Implement and fine-tune

    deep learning models

    for complex tasks such as image classification,

    computer vision

    , and

    natural language understanding

    .
  • Experiment with cutting-edge models like

    transformers

    (e.g.,

    BERT

    ,

    GPT

    ),

    CNNs

    , and

    RNNs

    .
  • Model Optimization and Tuning:

  • Optimize model performance using techniques such as

    hyperparameter tuning

    ,

    model ensembling

    , and

    cross-validation

    .
  • Assess and enhance the

    accuracy

    ,

    precision

    , and

    recall

    of models to ensure high-quality predictions.
  • Implement techniques for

    model deployment

    , including containerization using

    Docker

    or deploying models as REST APIs for integration.
  • AI System Integration:

  • Integrate AI models and machine learning algorithms into existing business systems and applications.
  • Work closely with software engineers and IT teams to deploy and scale AI solutions.
  • Design and develop

    data pipelines

    to automate the flow of data to and from AI systems.
  • Research & Innovation:

  • Stay up to date with the latest trends, methodologies, and advancements in AI, machine learning, and data science.
  • Conduct research and

    proof-of-concept

    experiments to explore new techniques and technologies that could benefit the organization.
  • Contribute to technical publications, blogs, and whitepapers on AI-related topics.
  • Collaboration & Support:

  • Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and business analysts.
  • Provide AI expertise and support for troubleshooting, optimization, and performance monitoring.
  • Assist in training and mentoring junior AI developers and other team members.
  • Documentation & Reporting:

  • Document AI models, codebases, and methodologies for future reference and maintenance.
  • Generate reports and visualizations to present model performance and results to stakeholders and leadership.

Required Qualifications:

  • 3-5 years

    of professional experience in

    Python programming

    and

    AI/ML development

    .
  • Strong knowledge of AI and machine learning concepts such as

    classification

    ,

    regression

    ,

    clustering

    ,

    deep learning

    , and

    reinforcement learning

    .
  • Hands-on experience with popular

    machine learning libraries

    like

    Scikit-Learn

    ,

    TensorFlow

    ,

    Keras

    ,

    PyTorch

    ,

    XGBoost

    , or

    LightGBM

    .
  • Proficiency in

    data manipulation

    and

    preprocessing

    using libraries like

    Pandas

    ,

    NumPy

    , and

    SciPy

    .
  • Experience working with

    deep learning frameworks

    (e.g.,

    TensorFlow

    ,

    Keras

    ,

    PyTorch

    ).
  • Strong understanding of

    neural networks

    ,

    CNNs

    ,

    RNNs

    , and

    transformer-based models

    (e.g.,

    BERT

    ,

    GPT

    ).
  • Solid experience in

    model evaluation

    and performance metrics such as

    accuracy

    ,

    precision

    ,

    recall

    ,

    F1-score

    , and

    AUC

    .
  • Familiarity with

    NLP

    techniques (e.g.,

    text preprocessing

    ,

    sentiment analysis

    ,

    text classification

    ) is a plus.
  • Experience in

    cloud platforms

    like

    AWS

    ,

    Azure

    , or

    Google Cloud

    for deploying AI models at scale.

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