Job Description Summary

Job Description

Core Responsibilities

• Developing and implementing advanced AI algorithms and models to solve complex problems across finance manufacturing quality supply chain sales & marketing.

• Developing and implementing advanced forecasting methodologies using technologies like batch forecasting deep learning simulation and reinforcement learning to enhance decision-making.

• Appling computer vision methods to drive manufacturing efficiencies and improve product quality across the GE Healthcare manufacturing network.

• Collaborating with cross-functional teams to integrate AI solutions into various applications and products.

• Analyzing large datasets to extract meaningful insights and improve model performance.

• Designing and conducting digital experiments to validate and optimize AI models.

• Presenting findings and recommendations to stakeholders in a clear and concise manner.

• Collaborating with the MLOps team during AI model development deployment and monitoring.

• Proactively identifying new opportunities to further leverage data science 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.

Experience Requirements

• M.S. or Ph.D. in Computer Science Data Science Engineering or a STEM related field with hands-on experience in developing and deploying AI models and applications.

• Proficiency in the latest Python AWS Azure and open-source data science tools such as Jupyter R SQL Hadoop Spark TensorFlow Keras PyTorch and Scikit-learn.

• Proficiency in AI agentic development tools such as AWS Bedrock Azure AI Foundry Microsoft Copliot Studio and LangChain/LangGraph.

• Knowledge of RAG architecture including retrieval mechanisms and generative models.

• Knowledge of deep learning architectures including CNNs RNNs and GANs.

• Experience building RAG models and AI agents via AWS or Azure AI services.

• Ability to work with large-scale datasets and perform efficient data analysis.

• Expertise in transformers self-supervised learning and generative AI models.

• 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.

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Pay Range

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.

Benefits & Rewards

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

Additional Information

Relocation Assistance Provided: No