IBM is looking to solve the business problem of helping leading companies across industries shape their hybrid cloud and AI journeys
Requirements
- 7–12+ years total experience in software engineering, data engineering, machine learning, or cloud architecture
- Hands-on experience in building and deploying ML models (supervised, unsupervised, deep learning)
- Model lifecycle & MLOps: MLflow, Kubeflow, Vertex AI, SageMaker
- Feature engineering and dataset management
- Large Language Models & Generative AI Experience
- Experience with LLM fine-tuning, RAG pipelines, vector databases
- Familiarity with OpenAI, Anthropic, Llama, Hugging Face
Responsibilities
- Innovative Systems Design for Optimal Performance: Design centralized or distributed systems that both address the user's requirements and perform efficiently and effectively
- End-to-End Data Architecture Leadership: Manage end-to-end data architecture, starting from selecting the platform, designing a technical architecture and developing the application
- Data Analysis and Insightful Reporting: Interpret data, analyze results using statistical techniques and provide ongoing reports discovering key insights
- Collaborate with client stakeholders and internal partners to understand the business problem and requirements, constraints of the system and concerns of the various stakeholders to systematically transform detailed solutions (architectures) for the client
- Guide the technical team to implementation
- Serve as a leader in defining solutions for clients
- Advocate for the client
Other
- 7–12+ years total experience
- Collaboration with client stakeholders and internal partners
- Long-term career development
- Unique skills and experiences valued
