IBM Infrastructure is a catalyst that makes the world work better because our clients demand it. Heterogeneous environments, the explosion of data, digital automation, and cybersecurity threats require hybrid cloud infrastructure that only IBM can provide.
Your ability to be creative, a forward-thinker and to focus on innovation that matters, is all support by our growth minded culture as we continue to drive career development across our teams. Collaboration is key to IBM Infrastructure success, as we bring together different business units and teams that balance their priorities in a way that best serves our client's needs.
The Infrastructure group is responsible for building and maintaining the components, tools, and systems that make up the Power, Z, Quantum Controls and Circuit Technologies. We are a large team spread across the world with a wide array of specialties and projects, working on everything from power management to silicon design.
IBM's product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive.
Responsibilities:
Required Professional and Technical Expertise :
• 3-5 years of experience working on AI solutions. Familiarity with GenAI, Deep Learning, Machine Learning - models (LLM, Faster R-CNN, RNN, LSTM, Transformers, XGBoost, Regression, etc.), frameworks (Tensorflow, PyTorch, ONNX, scikit-learn, etc.), and programming languages (Python, C/C++, JAVA, etc).
• 3-5 years of experience understanding solution requirements and architecting the AI solution. Experience in building and knowledge of end-to-end workflows for AI - Data acquisition; exploratory data analysis; model selection, development and tuning; model testing and validation & model deployment and governance.
• 2-3 years of experience working with clients and understanding theirs needs, use cases, ability to converse with Data scientists, analyze and understand customer application landscape.
• Knowledge of Data science software like IBM Cloud Pak for Data, Watsonx, Google Vizier, Azure AI Platform, H2O Driverless AI, etc.
Required Professional and Technical Expertise :
• 3-5 years of experience working on AI solutions. Familiarity with GenAI, Deep Learning, Machine Learning - models (LLM, Faster R-CNN, RNN, LSTM, Transformers, XGBoost, Regression, etc.), frameworks (Tensorflow, PyTorch, ONNX, scikit-learn, etc.), and programming languages (Python, C/C++, JAVA, etc).
• 3-5 years of experience understanding solution requirements and architecting the AI solution. Experience in building and knowledge of end-to-end workflows for AI - Data acquisition; exploratory data analysis; model selection, development and tuning; model testing and validation & model deployment and governance.
• 2-3 years of experience working with clients and understanding theirs needs, use cases, ability to converse with Data scientists, analyze and understand customer application landscape.
• Knowledge of Data science software like IBM Cloud Pak for Data, Watsonx, Google Vizier, Azure AI Platform, H2O Driverless AI, etc.
Preferred Professional and Technical Expertise :
• 2-3 years of experience working with Linux (RHEL) and working with Open-Source like Kubeflow, MLFlow, etc. Database programming skills - understanding of DBs like Oracle, DB2, SAP HANA + knowledge of how to write SQL queries for specific DBs
• 1-2 years of experience working with containers, RH Open Shift, orchestration, pipelines for building and deploying containers, Linux cmd line programming, etc.
2-3 years of experience working with clients understanding their pain points, and helping deploy AI solutions.
• Strong communication skills
• Growth minded, resourceful and a team-player.