GenAI Developer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a GenAI Developer with a contract length of "unknown," offering a pay rate of "unknown." Key skills include Python, .NET, and LLM experience. Candidates should have 5+ years in software engineering and familiarity with cloud-based AI environments.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
520
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πŸ—“οΈ - Date discovered
August 28, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
Unknown
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Plano, TX
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🧠 - Skills detailed
#Data Science #.Net #Azure #Agile #ML (Machine Learning) #AI (Artificial Intelligence) #Cloud #Deployment #Python #C#
Role description
Key Responsibilities β€’ Develop, integrate, and support GenAI-powered solutions using Python and .NET frameworks. β€’ Collaborate with engineering teams to address real-world challenges using LLMs (as consumers, not model creators). β€’ Apply deep problem-solving skills to engineer solutions β€” not just propose architectures. β€’ Scale AI models for enterprise-level performance, considering optimization, tokenization, and cost efficiency. β€’ Justify and implement tokenizer strategies and other AI engineering techniques for better model utility. β€’ Work cross-functionally with product owners, data scientists, and cloud engineers to deliver impactful GenAI solutions. β€’ Remain current with industry best practices and GenAI trends, adapting solutions accordingly. Required Skills & Qualifications β€’ 5+ years of software engineering experience with a strong focus on Python development. β€’ Solid working knowledge of .NET framework (C# or ASP.NET). β€’ Demonstrated experience in delivering solution-oriented AI implementations (not just model development). β€’ Hands-on experience with LLMs (e.g., OpenAI, Azure OpenAI, HuggingFace) in real-world applications. β€’ Strong understanding of tokenization, inference strategies, and model scaling principles. β€’ Ability to explain and justify engineering decisions to both technical and non-technical stakeholders. β€’ Comfortable working in agile, cross-functional environments with high accountability. Nice To Have β€’ Familiarity with cloud-based AI/ML environments (Azure preferred). β€’ Exposure to MLOps practices and deployment pipelines. β€’ Experience with prompt engineering, embedding models, or retrieval-augmented generation (RAG) Skills: genai,cloud-based ai/ml environments,mlops practices,solution-oriented ai implementations,accountability,python,agile methodologies,tokenization,ai engineering,llms,azure,cloud,.net