Staff AI Scientist
gehealthcare
Job Description
- Conduct advanced research in artificial intelligence, with focus areas including machine learning, deep learning, generative AI, large language models, natural language processing, GANs, multimodal AI, and agentic AI systems.
- Design, prototype, and validate novel AI algorithms, architectures, and workflows for real-world use cases.
- Explore and apply cutting-edge approaches in transformers, fine-tuning, retrieval-augmented generation (RAG), prompt optimization, autonomous agents, multi-agent systems, model alignment, and reasoning frameworks.
- Lead experimentation across model training, evaluation, benchmarking, and optimization.
- Stay current with emerging AI advances and translate academic research and industry innovation into scalable enterprise solutions.
- Publish research findings, contribute to patents, or create internal technical thought leadership that advances the organization’s AI maturity.
- Build, fine-tune, and optimize ML/DL models, including supervised, unsupervised, reinforcement, and self-supervised learning systems.
- Develop and deploy LLM-powered applications, conversational AI, summarization systems, semantic search, knowledge assistants, and intelligent automation platforms.
- Create Generative AI applications using foundation models for text, image, code, synthetic data, and multimodal outputs.
- Design and implement GAN-based solutions for synthetic data generation, image synthesis, anomaly simulation, data augmentation, and domain-specific generative use cases.
- Develop Agentic AI systems capable of task planning, tool usage, workflow orchestration, memory integration, retrieval, and decision support.
- Use AWS Bedrock to build and scale foundation model applications, including model access, orchestration, secure integration, and GenAI experimentation.
- Use AWS SageMaker for model training, tuning, experimentation, MLOps, deployment, and monitoring at scale.
- Work with structured and unstructured data across large-scale datasets to support AI research and production systems.
- Lead or collaborate on data cleaning, feature engineering, data quality improvement, dataset curation, and annotation strategies.
- Build robust AI pipelines that integrate with enterprise data systems, APIs, cloud services, and downstream applications.
- Apply SQL, NoSQL, database modeling, and data warehousing concepts to support efficient model training and inference.
- Partner with engineering teams to productionize models with scalability, observability, reliability, and security in mind.
- Ensure all AI systems are designed and deployed with strong Responsible AI principles.
- Develop practices for fairness, transparency, interpretability, explainability, privacy, accountability, and bias mitigation.
- Assess risks associated with foundation models, LLM outputs, hallucinations, model drift, adversarial misuse, and unsafe automation.
- Implement guardrails, evaluation standards, governance frameworks, and human-in-the-loop processes where necessary.
- Support compliance with evolving data privacy, security, and ethical AI requirements.
- Translate complex AI concepts into clear business value propositions for stakeholders, leadership teams, and non-technical audiences.
- Collaborate with product, engineering, security, legal, data, and business teams to define AI strategy and deliver measurable outcomes.
- Mentor junior scientists, ML engineers, and data professionals.
- Contribute to roadmap planning, architecture reviews, technical hiring, and AI capability development across the organization.
Required Qualifications
- PhD or Masters in Computer Science, Artificial Intelligence, Machine Learning, NLP, Data Science, or a related quantitative discipline.
- Strong research background with demonstrated contributions in AI/ML through publications, patents, applied research, industrial innovation, or equivalent scientific work.
- Deep knowledge of Machine Learning, Deep Learning, Natural Language Processing, Generative AI, Large Language Models, Agentic AI / AI Agents
- Proven experience developing advanced AI models from research through im