ML Lead

Role Overview: You are a highly skilled and innovative Machine Learning (ML) Lead with an entrepreneurial spirit, capable of excelling as both an individual contributor (IC) and a team leader. Your primary responsibility will be to lead ML initiatives, drive innovation, and build a new ML team while fostering a culture of mentorship and collaboration. Additionally, you will be involved in exploring and developing regulatory technology (RegTech) solutions, delivering impactful ML-powered systems, and managing projects from inception through deployment. Key Responsibilities: - Design, build, and implement machine learning models for various applications, including RegTech solutions, predictive analytics, natural language processing, and computer vision. - Foster innovation by testing and applying state-of-the-art algorithms and frameworks to tackle complex challenges. - Enhance models to ensure scalability, efficiency, and suitability for real-time deployment. - Create and oversee comprehensive ML pipelines covering data acquisition, preprocessing, model training, deployment, and ongoing monitoring. - Adopt MLOps best practices, including continuous integration/continuous deployment (CI/CD), model versioning, and production monitoring systems. - Establish and manage a high-performing machine learning team, providing mentorship, setting clear objectives, and cultivating a collaborative and innovative culture. - Proactively take responsibility for projects, seeking opportunities to deliver value through ML-based solutions. - Collaborate closely with product managers, engineers, and stakeholders to ensure machine learning initiatives align with business objectives and compliance requirements. - Conduct research to advance the use of machine learning within RegTech and other critical domains. - Maintain comprehensive documentation of models, pipelines, and workflows to ensure clarity, reproducibility, and knowledge sharing. Qualification Required: - Bachelors or Masters degree in Computer Science, Machine Learning, Data Science, or a related discipline (PhD preferred). - Over 7 years of experience in ML/AI, with a proven history of successful model deployment. - Preferred background or interest in RegTech/Fintech and applying ML solutions in these areas. - More than 3 years of experience in team leadership or mentorship, with demonstrated capability in team growth. - Proficiency with machine learning frameworks and tools. - Deep understanding of MLOps platforms (e.g., MLflow, Kubeflow) and cloud services (AWS, GCP, Azure). - Experienced in Python programming and familiar with big data technologies such as Spark and Hadoop. - Knowledge of regulatory and compliance systems is a plus. - Experience working with unstructured document data is advantageous. Additional Company Details: Weekday's client is focused on addressing challenges such as Identity Fraud Detection, Intelligent Document Processing, Motor Insurance & Finance, Contract Lifecycle Management, and User Knowledge Graph through advanced ML and RegTech solutions. Joining the team will provide you with opportunities to work on cutting-edge projects, lead and develop an ML team, innovate in a fast-paced industry, and be part of a collaborative environment with room for career advancement and a competitive salary and benefits package. Role Overview: You are a highly skilled and innovative Machine Learning (ML) Lead with an entrepreneurial spirit, capable of excelling as both an individual contributor (IC) and a team leader. Your primary responsibility will be to lead ML initiatives, drive innovation, and build a new ML team while fostering a culture of mentorship and collaboration. Additionally, you will be involved in exploring and developing regulatory technology (RegTech) solutions, delivering impactful ML-powered systems, and managing projects from inception through deployment. Key Responsibilities: - Design, build, and implement machine learning models for various applications, including RegTech solutions, predictive analytics, natural language processing, and computer vision. - Foster innovation by testing and applying state-of-the-art algorithms and frameworks to tackle complex challenges. - Enhance models to ensure scalability, efficiency, and suitability for real-time deployment. - Create and oversee comprehensive ML pipelines covering data acquisition, preprocessing, model training, deployment, and ongoing monitoring. - Adopt MLOps best practices, including continuous integration/continuous deployment (CI/CD), model versioning, and production monitoring systems. - Establish and manage a high-performing machine learning team, providing mentorship, setting clear objectives, and cultivating a collaborative and innovative culture. - Proactively take responsibility for projects, seeking opportunities to deliver value through ML-based solutions. - Collaborate closely with product managers, engineers, and stakeholders to ensure machine learning init