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  • Posted: Oct 30, 2024
    Deadline: Not specified
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    Indsafri started with a Vision - To be the best customer-centric & employee-friendly company; to build a one-stop shop in which all IT needs are fulfilled.
    Read more about this company

     

    AI/ML Engineer

    Key Responsibilities

    NLP Model Development & Deployment

    • Design, train, and deploy NLP models for a variety of tasks, such as text classification, sentiment analysis, named entity recognition, and language generation.
    • Leverage and fine-tune large language models (e.g., BERT, GPT, T5) for production use cases, ensuring efficiency and scalability.
    • Develop end-to-end NLP pipelines to streamline text processing, model training, and evaluation in production.

    Model Development & Deployment

    • Develop, train, and optimize machine learning models using industry-standard frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
    • Design and implement end-to-end ML pipelines to streamline data ingestion, model training, and evaluation.
    • Deploy machine learning models to production environments, ensuring robustness, scalability, and performance.

    Data Preparation & Engineering

    • Collaborate with data engineers to collect, clean, and preprocess data for training and evaluation purposes.
    • Work with large datasets, employing data engineering skills to handle data pipelines and structure data in ways that are conducive to model accuracy and efficiency.
    • Utilize big data technologies (e.g., Hadoop, Spark) to manage and analyse large volumes of data.

    Model Monitoring & Maintenance

    • Monitor models in production to ensure optimal performance, implementing retraining pipelines as necessary.
    • Troubleshoot, tune, and update models based on feedback from stakeholders, data drift, or changes in underlying data patterns.

    Collaboration & Communication

    • Work closely with data scientists, software engineers, and product teams to align AI models with business goals.
    • Translate complex technical findings into actionable insights for non-technical stakeholders.

    Research & Development

    • Stay updated with the latest advancements in AI/ML technology and best practices, applying relevant developments to current projects.
    • Experiment with new algorithms, techniques, and tools that can improve model performance and solve new challenges.

    Key Skills & Qualifications

    • Educational Background: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field.

    Technical Skills:

    • Proficiency in Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Keras).
    • Solid understanding of ML algorithms and techniques (e.g., supervised/unsupervised learning, deep learning, reinforcement learning).
    • Experience with data processing libraries (e.g., Pandas, NumPy) and visualization tools (e.g., Matplotlib, Seaborn).
    • Familiarity with big data technologies (e.g., Hadoop, Spark) and database systems (SQL and NoSQL).

    Mathematics & Statistics: Strong foundation in linear algebra, calculus, probability, and statistics.

    • Software Development: Knowledge of software engineering best practices, including code versioning, unit testing, and CI/CD pipelines.
    • Problem-Solving & Analytical Skills: Ability to troubleshoot complex ML model issues and optimize for performance.
    • Communication: Ability to convey complex technical information to non-technical stakeholders effectively.

    Preferred Qualifications

    • Familiarity with cloud platforms (AWS, Azure, Google Cloud) and ML services (e.g., SageMaker, Azure ML).
    • Experience in natural language processing, computer vision, or other specialized AI domains.
    • Knowledge of MLOps practices for model lifecycle management and scalability.
    • Prior experience in a similar AI/ML engineering role.

    Method of Application

    Interested and qualified? Go to IndSAfri on www.linkedin.com to apply

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