Core Responsibilities
Leading development of AI-driven solutions including but not limited to:
1) Designing RAG models agent workflows and multi-step reasoning models.
2) Unstructured data analysis.
3) Integrating ML/GenAI models and LLM orchestration into end-user AI applications.
4) Conducting research and staying updated with the latest advancements in AI technologies.
5) Translating AI research into business solutions.
Collaborating with cross-functional teams to integrate AI solutions into various applications and products.
Analyzing large datasets to extract meaningful insights and improve AI model performance.
Designing and conducting experiments to validate and optimize AI models.
Presenting findings and recommendations to stakeholders in a clear and concise manner.
Collaborating with the MLOps & AIOps teams to establish standards for AI model development deployment and monitoring.
Proactively measuring and communicating value generation from developed AI solutions to business and IT leaders across GE HealthCare.
Proactively identifying new opportunities to further leverage AI solutions prioritizing opportunities with the biggest potential benefit to the business.
Ensuring best practice adoption within the Enterprise AI team applying appropriate levels of technical capability standardization and subject matter expertise.
Driving a culture of analytics and fact-based decision making through the utilization of standard methodologies and approaches.
Operating as a thought leader and visionary with the ability to influence executive leaders in the strategic use of ML AI GenAI and advanced analytics in decision-making and value creation.
Requirements
PhD in Computer Science Data Science Engineering or a STEM related field with a focus on neural networks and computer vision.
Hands-on experience in developing and deploying AI models and applications.
Deep expertise in the latest AI tools and platforms such as MCP A2A AWS Bedrock Azure AI Foundry LLM foundational models and agentic orchestration & monitoring platforms such as LangGraph/LangSmith.
Deep expertise in GenAI model development AI Agent design and orchestration Computer Vision Deep Learning Transformers Self-Supervised Learning and LLM fine tuning.
Experience implementing transformers self-supervised learning and generative AI models in reliable maintainable APIs or microservices.
Ability to work with large-scale datasets and perform efficient data analysis.
Expertise in transformers self-supervised learning and generative AI models.
Ability to continuously track evaluate adapt the latest advancements in AI technology to business use cases across GE HealthCare.
Strong problem-solving skills and the ability to think critically and creatively.
Excellent communication skills and the ability to work collaboratively in a team environment.
#LI-MT1
#LI-Hybrid
Placement within this range depends on:
Relevant skills and qualifications
Prior job-related experience
Internal equity considerations (alignment with colleagues in similar roles) e.t.c.
We review pay ranges regularly to ensure they remain competitive with the external market and align with our internal equity considerations.
In addition to base salary our employees have access to a comprehensive package of benefits and allowances which may include:
Health & wellness coverage
Retirement and or savings plans
Allowances or benefits to support role requirements (e.g. mobility transport or role-specific needs such as a company car or allowance where applicable)
Work-life balance support (e.g. flexible working leave programs)
Recognition and incentive programs aligned with performance and company success
The exact benefits package depends on the role location and employment terms as specified in the Colleague Value Proposition document that will be shared prior to the interview or at the offer discussion stage.
Performance Bonus: Details to be shared during offer discussions
Relocation Assistance Provided: Yes
Required Experience:
Staff IC
GE HealthCare provides digital infrastructure, data analytics & decision support tools helps in diagnosis, treatment and monitoring of patients