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Cognyte Bulgaria

Senior Machine Learning Engineer

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    Tech Stack / Requirements

    Today’s world is crime-riddled. Criminals are everywhere, invisible, virtual and sophisticated. Traditional ways to prevent and investigate crime and terror are no longer enough…

    Technology is changing incredibly fast. The criminals know it, and they are taking advantage. We know it too.

    For 30 years, the incredible minds at Cognyte around the world have worked closely together and put their expertise to work, to keep up with constantly evolving technological and criminal trends and help make the world a safer place with leading investigative analytics software solutions.

    We are defined by our dedication to doing good and this translates to business success, meaningful work friendships, a can-do attitude, and deep curiosity.

    Our product:

    Our analytics platform powers our portfolio. Data is growing rapidly and is highly fragmented across different departments, and organizations are looking to adopt open software to keep up with the pace of technology. These market shifts require security organizations to deploy an analytics platform that can connect different solutions from either Cognyte or third parties to effectively develop new capabilities.

    We are currently looking for an exceptional and passionate Senior Machine Learning Engineer to join our Fusion Analytics team in Bulgaria.

     

    As a Cognyter you will:

     

    • Research and Design Machine Learning models in Computer Vision / NLP to solve business challenges and meet product goals
    • Extract, transform and load raw data into formats suitable for model training
    • Train, evaluate and optimize Machine Learning models for both accuracy and scalability
    • Productionize Machine Learning models as containerized microservices with high-quality, modular code, following best practices for deployment and monitoring
    • Deploy Machine Learning models on cloud-native infrastructure, including Google Kubernetes Engine (GKE) and on-prem Kubernetes clusters
    • Design and implement an end-to-end Machine Learning pipeline infrastructure

     

    For that mission you’ll need:

     

    • Bachelor’s and/or Master’s degree in IT engineering, physics, bioinformatics, mathematics, data science or similar field (or equivalent experience)
    • 3+ years’ experience in similar positions, working with Deep Learning and/or traditional Machine Learning models
    • 3+ years’ experience building microservices using Python and frameworks such as FastAPI/Flask/Django
    • Experience with data analysis tools such as: pandas, NumPy, Matplotlib, Jupyter/Colab
    • Experience with distributed systems, microservice architectures and cloud native platforms

     

    Tech stack:

     

    • Infra: Git, Bash
    • Containers: Docker
    • Machine Learning frameworks: Scikit-learn
    • Deep Learning frameworks: TensorFlow/PyTorch/Hugging Face
    • MLOps: Kubeflow, MLflow, Helm, Kubernetes, CI/CD pipelines

     

    Nice to have:

     

    • Related personal projects in Github/Kaggle or similar platforms
    • Finished courses in Machine Learning and/or Deep Learning
    • Understanding of deep learning model architectures: Transformers, CNNs, RNNs (LSTM/GRU)
    • Knowledge of (Graph)-RAG (Retrieval-Augmented Generation) and Agents

     

    Remember: When you’re curious enough, you don’t need to check every box to apply. Be in touch!

     

    We believe that diverse teams drive the greatness of ideas, products, and companies. Whatever your gender, age, race, creed, or taste in music – if you’re curious enough, you don’t need to check every box to apply. We’re waiting for you. Apply now.