Lead Data Engineer -ML Ops

• AI/ML & Data Pipeline / AI/ML Model Deployment • Design, build, and maintain pipelines that support the development and maintenance of AI/ML models, data ingestion, transformation, and storage of large-scale datasets. • Optimize data workflows to ensure efficient data processing and availability. • Develop and implement best practices for deploying, monitoring, and managing robust data and analytics pipelines and AI/ML models in production. • Collaborate with data scientists to ensure seamless integration and deployment of AI/ML solutions. • Strategy and Planning • Define the vision, strategy, and roadmap for data engineering and MLOps/AgentOps in alignment with the company's goals. • Ensure the scalability, reliability, and efficiency of AI/ML models and data pipelines. • Team Leadership and Development • Lead and motivate a high-functioning engineering team, providing coaching to empower members and delivery squads. • Encourage innovation, experimentation, and best practices within the data engineering team. • Allocate resources, manage workloads, and set goals to ensure timely, budget-compliant project completion. • Security and Compliance • Ensure that data engineering and MLOps/AgentOps processes adhere to industry standards, regulatory requirements, and security best practices. • Implement measures to safeguard sensitive data and protect against potential vulnerabilities • Continuous Improvement • Stay updated on the latest advancements in data engineering and MLOps/AgentOps technologies and methodologies. • Implement best practices and drive continuous improvement initiatives to enhance the efficiency and effectiveness of our AI/ML systems. • What will you need to succeed in this role: • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Software Engineering or a related field. • Demonstrated experience (5+ years) in data engineering, machine learning operations, or related fields, including team leadership or mentoring role. • Advanced proficiency in programming languages such as Python, Java, or Scala. Comprehensive knowledge of data pipeline frameworks (e.g., Databricks) and MLOps tools (e.g., MLflow, Kubeflow). • Extensive hands-on experience with cloud platforms (e.g., AWS, Google Cloud, Azure), CI/CD pipelines, containerization/orchestration tools (e.g., Docker, Kubernetes). • Exceptional problem-solving and analytical skills, with in-depth expertise in MLOps/AgentOps architecture, data modeling, and database systems. • Strong leadership and team management capabilities, with the ability to motivate and inspire team members. Excellent communication and interpersonal proficiency. • Ability to excel in a fast-paced and dynamic environment. Proven adaptability and eagerness to adopt new technologies and methodologies. • High attention to detail and a commitment to delivering high-quality solutions. Ability to prioritize tasks and manage multiple projects concurrently. • The expected base salary range for this position is $ 97,500.00 - $ 147,500.00. Depending on your relevant experience, skills, qualifications, market conditions and business needs, base compensation may vary. You have the potential to earn more through Gore Mutual’s discretionary bonus program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.