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AI Engineer

AI Engineer

IBM

1 - 5 years

8 - 12 Lacs

ahmedabad

Posted:None| Platform:

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Skills Required

python artificial intelligence tensorflow pytorch ml algorithms emerging technologies natural language processing neural networks microsoft azure machine learning data engineering deep learning data science gcp devops computer vision 48464 agile aws

Work Mode

Work from Office

Job Type

Full Time

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 texts, image and other data.

Leverage Retrieval-Augmented Generation (RAG) techniques to enhance AI-driven insights and decision-making.

Enterprise Software Integration:

Integrate AI models with Enterprise Software to build high-quality AI use-cases.

Develop custom AI algorithms and AI Agents.

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 Preferred education Master's Degree Required technical and professional expertise

5+ years of experience.
Programming Expertise:

Proficient in Python with demonstrated experience in AI and ML development. Knowledge of vector database.

AI Agents, GenAI and LLMs:

Strong expertise in GenAI concepts, including the design, deployment, and optimization of Large Language Models (LLMs) and design AI Agents.

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.

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