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As Senior Director of MLOps, you will be responsible to drive functional excellence in enterprise MLOps through scalable and reliable ML, AI, and GenAI solutions aligned with strategic direction of GE HealthCare. You will be reporting to the Head of Enterprise AI.
As leader of the group, youwill be responsible for defining the strategic objectives and requirements of ML, AI, and GenAI Operations that will accelerate insight generation and create business value for the enterprise. You will partner with leaders in Integrated Supply Chain & Service, Finance, Commercial, and other groups to identify business needs that shape this strategy. They will work across IT to develop state-of-the-art AI/GenAI MLOps capabilities to address the identified needs. In addition, this position will hire and lead a team of ML Engineers.
Key Responsibilities
Leading the design and implementation of MLOps strategies and frameworks that ensure efficient model deployment, monitoring, and maintenance for Enterprise ML, AI, and GenAI solutions that create value for GE HealthCare.
Establishing best practices for model lifecycle management, including versioning, testing, monitoring, and retraining of models
Overseeing the deployment of models into production environments, ensuring robust monitoring systems are in place for performance tracking and anomaly detection.
Operating as a thought leader and visionary, with the ability to evangelize strategic use of ML, AI, GenAI, and advanced analytics in decision-making and value creation
Developing the ML, AI, and GenAI roadmap, including constant evaluation and incorporation of valuable data assets, technologies and methodologies.
Acting as a Change Agent who effectively communicates the vision and implementation roadmap for the new analytical capabilities and who gains buy in from stakeholders across the organization.
Building and leading a team of ML engineers who will create business value through scalability and relatability of ML, AI, GenAI, and advanced analytics solutions.
Developing a culture and environment where ML Engineers thrive, overseeing the development of competency models, career paths, and onboarding and training programs for the individuals in the group.
Collaborating with existing analytics teams, as well as key stakeholders, to identify existing, or new, areas that can benefit significantly from AI, GenAI, and advanced analytics.
Collaborating across IT and STO functions to ensure that technology enables ML, AI, GenAI, and advanced analytics capabilities and that data and algorithms are reliable and accurate
Serving as a key member of working groups developing digital platforms, as well as ensuring that data from these platforms can be appropriately utilized for insight generation.
Staying abreast of market evolutions and dynamics regarding GE HealthCare’s position in industry and therapeutic areas
Required Qualifications
We seek an accomplished leader, with demonstrated success in leading teams and guiding key decisions through analytical insight. Specifically, they will possess the following:
Masters/PhD in Engineering, Data Science, AI, Statistics, or related graduate-level degree,
Strong healthcare data and analytics experience, including management experience,
Previous experience in leading & managing analytical consulting, or related functions,
Excellent team management, coaching and mentoring skills.
Superior planning, process and influencing skills,
Demonstrated ability to be an effective change management leader for direct reports,
Exceptional structured problem-solving and strategic agility abilities,
Deep knowledge of AI, GenAI, and advanced analytics and technologies and methodologies, as well as proven experience translating data into business value,
Strong understanding of machine learning frameworks, tools, and practices (e.g., TensorFlow, PyTorch, MLflow, Kubeflow),
Proven experience in deploying machine learning models at scale in production environments, preferably in the Healthcare or MedTech sector,
Experience with AI, GenAI, and advanced analytics tools (R, Python, SageMaker, RedShift, CoPilot, ChatGPT), data technologies, cloud computing environments (AWS, Google Cloud, Azure), and containerization technologies (Docker, Kubernetes).
Deep knowledge of business analytics and associated practices relevant to the healthcare/MedTech/pharmaceutical/biotech industries.
Proven track record for consistently meeting or exceeding qualitative, as well as any relevant quantitative, targets and goals.
Ability to communicate AI, GenAI, statistical and technical ideas and results to non-technical clients in written and verbal form, including experience and level of comfort presenting concepts to senior executives.
Ability to travel (ad hoc).
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