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) Conduct research and stay updated with the latest advancements in AI technologies.
5) Translate AI research into business solutions.
Project Execution: Leading and contributing to AI engineering projects from ideation through implementation ensuring solutions are robust scalable and aligned with organizational priorities.
Cross-Functional Collaboration: working closely with colleagues in data engineering ML engineering data science analytics GenAI and business stakeholders to deliver integrated solutions and drive project success.
Technical Excellence: applying best practices in data preparation feature engineering model selection validation and deployment. Participate in code reviews and contribute to technical documentation.
Continuous Improvement: staying current with advancements in ML GenAI and analytics. Proactively identify opportunities to improve existing models and processes.
Business Impact: translating complex AI engineering concepts into actionable insights for business partners supporting decision-making and measurable outcomes.
Mentorship & Learning: sharing knowledge with peers contribute to team learning and seek opportunities for professional growth.
Requirements
Experience: Bachelors Masters or PhD degree in Computer Science AI Data Science Engineering Applied Mathematics or related field with direct AI/ML experience in industry with demonstrated success building and deploying enterprise-grade solutions at scale.
Relevant Expertise: Proven ability to apply AI to solve real-world problems in areas such as forecasting pricing customer analytics sales planning computer vision and operational optimization
Technical Skills: 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.
Expertise in GenAI model development AI Agent design and orchestration Computer Vision Deep Learning Transformers Self-Supervised Learning and LLM fine tuning.
Industry Knowledge: Understanding of analytics practices relevant to commercial operations logistics inventory management manufacturing and finance.
Communication Skills: Strong ability to convey complex technical concepts to non-technical stakeholders and senior executives.
Interpersonal Skills: Proven success working in cross-functional hybrid and virtual teams.
Ethics & Integrity: Commitment to ethical data science practices.
Travel: Willingness to travel for business meetings as needed.
#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