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Manager AI/ML
Syncron
Warsaw, USA
Manager · 20+ years experience
Hybrid
Discovered 1 weeks ago
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Role Overview
We are seeking a Manager/Senior Manager AI& ML to lead a high-impact team of data scientists, ML engineers, and AI specialists in building cutting-edge AI/ML solutions. This role requires a blend of technical expertise in DS, AI/ML, MLOps, with strong leadership capabilities. The ideal candidate will have a proven track record of deploying scalable AI/ML systems and fostering a high-performing, innovative team culture
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About the role
We are seeking a Manager/Senior Manager AI& ML to lead a high-impact team of data scientists, ML engineers, and AI specialists in building cutting-edge AI/ML solutions. This role requires a blend of technical expertise in DS, AI/ML, MLOps, with strong leadership capabilities. The ideal candidate will have a proven track record of deploying scalable AI/ML systems and fostering a high-performing, innovative team culture
What would you do?
Strategic Leadership: Develop and execute the organization's data science strategy, with a strong focus on advancing machine learning, MLOps, and AutoML practices to optimize operational workflows and model lifecycle management.
Team Management: Lead, mentor, and grow a dynamic team of data scientists, ML engineers and specialists, fostering a collaborative and innovative work environment.
Define and evolve the long-term AI/ML architecture roadmap, ensuring scalability, maintainability, and integration with existing systems.
Data Strategy: Define and implement a roadmap for data collection, storage, and analysis, emphasizing the integration of machine learning pipelines, scalable MLOps frameworks, and AutoML systems for accelerated model development.
Advanced Analytics: Oversee the deployment of predictive models, machine learning algorithms, and statistical analyses, ensuring the seamless integration of AutoML platforms for enhanced efficiency and scalability.
Model Lifecycle Enhancement: Focus on improving model lifecycle time and scalability by implementing cutting-edge practices in MLOps and AutoML to reduce time-to-market and ensure robust, adaptable solutions.
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