We are seeking a highly experienced Machine Learning Lead Engineer to drive the design, development, and deployment of advanced machine learning models and AI-driven solutions. This role involves leading technical strategy, guiding data science initiatives, and working closely with cross-functional teams to deliver scalable and efficient machine learning systems. The ideal candidate will bring strong leadership, hands-on engineering expertise, and a deep understanding of modern machine learning technologies and tools.
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Lead the development, training, testing, and deployment of machine learning and deep learning models.
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Architect and implement scalable ML pipelines and production-grade systems.
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Collaborate with data engineers, product managers, and software developers to integrate ML capabilities into applications.
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Manage model performance, optimization, drift monitoring, and continuous improvements.
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Evaluate new algorithms, technologies, and frameworks to enhance system performance.
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Oversee the end-to-end ML lifecycle, including feature engineering, data preprocessing, and dataset management.
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Guide and mentor junior team members, promoting best practices and code quality.
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Document architecture, workflows, and research findings.
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Ensure security, compliance, and reliability of data and models.
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Work directly with business stakeholders to translate requirements into technical ML solutions.
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Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
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12+ years of experience in machine learning engineering, data science, or AI solution design.
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Expertise in machine learning algorithms, deep learning architectures, and statistical modeling.
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Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and Keras.
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Hands-on experience building production ML pipelines using tools like Kubernetes, Docker, Airflow, or MLflow.
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Strong knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
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Experience with large-scale data processing using Spark, Hadoop, or similar technologies.
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Proficiency in SQL and NoSQL databases.
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Ability to present technical concepts to both technical and non-technical stakeholders.
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Strong problem-solving skills, analytical thinking, and team leadership abilities.