Machine Learning Engineering Lead

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Requirements:

• 7+ years of experience in machine learning or data science roles, with at least 3 years in a leadership position
• Strong proficiency in programming languages such as Python, R, or Java, and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Proven track record of successfully deploying ML models into production environments
• Experience with cloud-based ML platforms (e.g., AWS Sagemaker, Google AI Platform) and MLops practices
• Solid understanding of machine learning algorithms, statistical methods, and data preprocessing techniques
• Excellent leadership and team management skills with the ability to inspire and motivate team members
• Strong problem-solving skills and the ability to work collaboratively in a fast-paced environment
• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders
• A degree in Computer Science, Engineering, Data Science, or a related field (Master’s or Ph.D. is a plus)

Responsibilities:

• Lead and mentor a team of machine learning engineers, providing technical guidance and fostering a collaborative environment
• Design, implement, and oversee the entire ML lifecycle, from data preparation to model deployment and monitoring
• Collaborate with cross-functional teams to define project goals, communicate progress, and ensure alignment with business objectives
• Stay abreast of industry trends and advancements in ML and data science, integrating new technologies and methodologies as appropriate
• Drive continuous improvement in ML processes and practices, ensuring high standards of model performance, accuracy, and interpretability