Lead ML Engineer

We are seeking a highly skilled Lead Machine Learning Engineer to drive advanced AI and machine learning initiatives within our banking and finance operations. This hands‑on leadership role demands technical excellence, project ownership, and the ability to communicate complex concepts to diverse stakeholders. The ideal candidate will bring deep expertise in developing and deploying machine learning solutions, particularly in regulated financial environments. Required Skills and Experience: Minimum 10 years of hands‑on experience in machine learning, artificial intelligence, or data science roles . Demonstrated experience in the banking or finance sector, with a strong understanding of regulatory compliance. Advanced programming proficiency in Python, R, or Scala. Expertise in leading ML libraries and frameworks: TensorFlow, PyTorch, Scikit‑learn . Experience working with big data technologies such as Hadoop and Spark . Solid knowledge of SQL and/or NoSQL database systems. Background in risk modeling, capital models, and regulatory frameworks relevant to banking. Practical experience with ML ops tools (Docker, Kubernetes, MLflow, Kubeflow, Airflow). Strong skills in statistical modeling, optimization techniques, and feature engineering . Exceptional ability to communicate technical concepts and results to non-technical audiences. Key Responsibilities: Lead end-to-end machine learning projects, from problem definition through deployment and monitoring. Design, develop, and implement robust predictive models and risk modeling frameworks for banking and capital management. Collaborate with data engineers, analysts, and business units to identify opportunities for machine learning applications. Ensure all ML solutions comply with industry regulations and internal risk management standards. Oversee the operationalization of models using ML ops tools (Docker, Kubernetes, MLflow, Kubeflow, Airflow). Present findings, model outcomes, and recommendations clearly to non-technical stakeholders and senior management. Mentor junior team members and foster best practices in statistical modeling, feature engineering, and optimization. Cloud Hybrid is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. Cloud Hybrid will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will Cloud Hybrid require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract #J-18808-Ljbffr