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1 Week ago
SecNinjaz Technologies - Artificial Intelligence/Machine Learning Engineer - Tensorflow/PyTorch
Vellore, Tamil Nadu, India
Information Technology
Full-Time
SecNinjaz Technologies LLP
Overview
Job Description
- Design, develop, and implement machine learning models and algorithms for various applications (e.g., natural language processing, computer vision, predictive analytics, recommendation systems).
- Build and maintain scalable and robust AI/ML pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
- Utilize cloud-based AI/ML platforms and services (e.g., AWS SageMaker, Google AI Platform, Azure Machine Learning) to build and deploy solutions.
- Work with large datasets, perform data exploration and analysis, and identify relevant features for model development.
- Evaluate model performance using appropriate metrics and iterate on models to improve accuracy and generalization.
- Stay up-to-date with the latest advancements in AI/ML research and technologies.
- Collaborate with data engineers, software engineers, and domain experts to integrate AI/ML models into production systems.
- Develop and maintain clear and concise documentation for AI/ML models and pipelines.
- Participate in code reviews and contribute to best practices in AI/ML development.
- Troubleshoot and debug AI/ML models and systems.
- Communicate findings and insights effectively to both technical and non-technical audiences.
- Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
- Specify Experience Range - e.g., 2-5+ years] of proven experience as an AI/ML Engineer or a similar role.
- Strong programming skills in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Keras, NumPy, Pandas).
- Solid understanding of machine learning algorithms (e.g., regression, classification, clustering, deep learning, reinforcement learning).
- Experience with data preprocessing, feature engineering, and data visualization techniques.
- Familiarity with cloud-based AI/ML platforms and services (e.g., AWS, Azure, GCP).
- Experience with deploying and scaling machine learning models in production environments.
- Strong understanding of statistical concepts and model evaluation metrics.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills
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