AI Architect
Job Description
Qualifications and Requirements:
- Bachelors or master's degree in computer science, Engineering, or a related field. A Ph.D. in AI or Machine Learning is a plus.
- Proven experience as an AI Engineer, Machine Learning Engineer, or AI Architect, with a track record of successful AI solution design and implementation.
- Streamlit -- Python
- Generative AI
- HuggingFace , OpenAi and any Custom Model development experience
- Strong programming skills in languages such as Python, Java, or C++, and proficiency in AI libraries and frameworks (TensorFlow, PyTorch, scikit-learn, etc.).
- In-depth knowledge of machine learning techniques, algorithms, and model evaluation.
- Familiarity with big data technologies, cloud platforms, and distributed computing.
- Excellent problem-solving abilities and analytical thinking.
- Effective communication skills to collaborate with cross-functional teams and present technical concepts to both technical and non-technical stakeholders.
- Demonstrated ability to lead technical projects, drive innovation, and mentor junior team members.
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Key Skills
About Company
Skills:
Machine Learning, Sql, Gcp, MLops, Azure, Python, AWS, Data lakes, LLM ecosystems, GenAI, Deep Learning frameworks, AI deployment frameworks, R, AI governance
Skills:
AWS, Node.js, FastAPI, Python, Azure, Jira, Gcp, Multi-cloud AI platform architecture, AI Governance, Generative AI
Skills:
Python, Agentic AI, Multi-Agent Systems, Generative AI, LLMs, Prompt Engineering, Reasoning Frameworks, RAG, Retrieval-Augmented Generation
Skills:
Java, Nlp, Git, Python, AI Architecture, embeddings, vector search, RAG patterns, AI Fundamentals, Evaluation, cloud-based delivery, retrieval, NLU
Skills:
solution architecture, Data Integration, automation, Cloud Technologies, Security, model and tool integration, generative AI, AI engineering, enterprise AI technology platforms, production technology delivery