Machine Learning Architect
3 weeks ago
Responsibilities:
• Design and develop the architecture for Client platforms and solutions.
• Select and implement appropriate Client algorithms and tools based on business requirements and data characteristics.
• Collaborate with data scientists, data engineers, and software engineers to ensure the successful integration of Client models into production systems.
• Oversee data pipelines and ensure data quality for training and deploying Client models.
• Monitor and evaluate the performance of Client models, identifying opportunities for improvement and retraining.
• Stay up-to-date on the latest advancements in Client research and best practices.
• Develop and implement strategies for managing model bias and ensuring the ethical use of AI.
• Communicate complex technical concepts to both technical and non-technical stakeholders.
• Mentor and guide junior team members on Client architecture best practices.
Qualifications:
• Master's degree in Computer Science, Engineering, or a related field (or equivalent experience).
• Strong understanding of machine learning concepts, algorithms, and frameworks.
• Experience designing and developing scalable, distributed systems.
• Experience with cloud platforms (AWS, Azure, GCP) is a plus.
• Excellent communication and collaboration skills.
• Proven ability to translate business goals into technical requirements.
• Experience working in an Agile development environment is a plus.
Tools and Technologies (possible, depending on the company):
• Python (Scikit-learn, TensorFlow, PyTorch)
• Machine Learning Platforms (AWS SageMaker, Azure Machine Learning, Google AI Platform)
• Cloud Computing Technologies (AWS, Azure, GCP)
• Docker, Kubernetes
• DevOps Tools (Git, Jenkins, CI/CD pipelines).
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