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AI Engineer
IBM
posted 20d ago
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Key skills for the job
Job Description
- AI Development and Implementation:
- Design, develop, and deploy cutting-edge AI solutions using GenAI technologies.
- Implement and optimize Large Language Models (LLMs) for natural language processing (NLP) applications.
- Leverage Retrieval-Augmented Generation (RAG) techniques to enhance AI-driven insights and decision-making.
- Requirements Quality Management:
- Integrate AI models with Requirements Management Software tool to ensure high-quality requirements management.
- Develop custom AI algorithms to automate requirement validation, improve quality, and detect inconsistencies.
- Solution Optimization and Integration:
- Fine-tune NLP models to align with domain-specific needs and improve accuracy.
- Collaborate with cross-functional teams to integrate AI solutions into enterprise workflows.
- Mentorship and Leadership:
- Mentor junior developers on AI best practices, tools, and frameworks.
- Lead brainstorming sessions to explore innovative AI applications and solutions.
- Research and Innovation:
- Stay updated with the latest advancements in AI, GenAI, LLMs, and RAG to continuously enhance systems.
- Conduct proof-of-concept projects to evaluate emerging technologies for business use cases.
Required education
Bachelor's Degree
Required technical and professional expertise
- Programming Expertise:
- Proficient in Python with demonstrated experience in AI and ML development.
- GenAI and LLMs:
- Strong expertise in GenAI concepts, including the design, deployment, and optimization of Large Language Models (LLMs).
- NLP Skills:
- Advanced knowledge of NLP techniques for text analysis, summarization, and contextual understanding.
- RAG Expertise:
- Hands-on experience with Retrieval-Augmented Generation (RAG) to enhance knowledge retrieval systems.
- Tools and Frameworks:
- Proficiency with AI frameworks like TensorFlow, PyTorch, Hugging Face, or similar.
Familiarity with cloud platforms (AWS, Azure, GCP) for deploying AI solutions.
Preferred technical and professional experience
- DevOps and MLOps:
- Knowledge of deploying AI models in production environments using MLOps best practices.
- Data Engineering:
- Familiarity with data preparation, preprocessing pipelines, and working with unstructured datasets.
- Agile Methodologies:
- Experience working in Agile development environments for iterative delivery.
- Soft Skills:
Strong problem-solving skills, attention to detail, and ability to communicate complex concepts to technical and non-technical stakeholders.
Employment Type: Full Time, Permanent
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AI Engineer salary at IBM
reported by
75
employees
with 2-7
years exp.
Unlock
₹14.2
L/yr - ₹44
L/yr
105%
more
than the average AI Engineer Salary in India
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