FitNext Co.
Generative AI Engineer Onsite at Alpharetta GA
FitNext Co., Alpharetta, Georgia, United States, 30239
Job Title:
Generative AI Engineer
Location:
Onsite – Alpharetta, GA
Employment Type:
Full-Time
Experience Level:
Senior
** **
About the Role We are seeking a highly skilled and motivated
Generative AI Engineer
to design, develop, and deploy cutting-edge AI solutions leveraging Large Language Models (LLMs), multimodal transformers, and generative algorithms. You will work on innovative applications across content creation, chat interfaces, autonomous agents, and intelligent data synthesis. This is a high-impact role where your work will help shape next-generation AI capabilities.
** **
Key Responsibilities
Develop and fine-tune LLMs (e.g., GPT, LLaMA, Mistral, Claude) for custom downstream tasks.
Implement and optimize RAG (Retrieval-Augmented Generation) pipelines using LangChain, LlamaIndex, or Haystack.
Build end-to-end Generative AI applications for text, code, images, and audio.
Leverage vector databases (FAISS, Pinecone, Weaviate, Qdrant) for embedding-based retrieval.
Integrate APIs from foundation models (OpenAI, Anthropic, Cohere, HuggingFace) into product workflows.
Work with multimodal models and techniques (CLIP, DALL·E, Stable Diffusion, Gemini).
Optimize model performance, latency, and scalability in production environments.
Collaborate cross-functionally with ML, data, and product teams to identify and implement use cases.
Stay current with advancements in generative AI and proactively apply them.
** **
Required Qualifications
Bachelor's or Master's degree in Computer Science, Machine Learning, or related field.
Proven experience in ML/AI engineering with strong expertise in generative AI or LLMs.
Proficiency in Python and experience with frameworks such as Transformers (HuggingFace), LangChain, PyTorch, or TensorFlow.
Strong understanding of NLP, deep learning, and transformer architectures.
Experience building scalable ML pipelines and deploying models to production (Docker, Kubernetes, etc.).
Familiarity with prompt engineering, fine-tuning, and model evaluation techniques.
Generative AI Engineer
Location:
Onsite – Alpharetta, GA
Employment Type:
Full-Time
Experience Level:
Senior
** **
About the Role We are seeking a highly skilled and motivated
Generative AI Engineer
to design, develop, and deploy cutting-edge AI solutions leveraging Large Language Models (LLMs), multimodal transformers, and generative algorithms. You will work on innovative applications across content creation, chat interfaces, autonomous agents, and intelligent data synthesis. This is a high-impact role where your work will help shape next-generation AI capabilities.
** **
Key Responsibilities
Develop and fine-tune LLMs (e.g., GPT, LLaMA, Mistral, Claude) for custom downstream tasks.
Implement and optimize RAG (Retrieval-Augmented Generation) pipelines using LangChain, LlamaIndex, or Haystack.
Build end-to-end Generative AI applications for text, code, images, and audio.
Leverage vector databases (FAISS, Pinecone, Weaviate, Qdrant) for embedding-based retrieval.
Integrate APIs from foundation models (OpenAI, Anthropic, Cohere, HuggingFace) into product workflows.
Work with multimodal models and techniques (CLIP, DALL·E, Stable Diffusion, Gemini).
Optimize model performance, latency, and scalability in production environments.
Collaborate cross-functionally with ML, data, and product teams to identify and implement use cases.
Stay current with advancements in generative AI and proactively apply them.
** **
Required Qualifications
Bachelor's or Master's degree in Computer Science, Machine Learning, or related field.
Proven experience in ML/AI engineering with strong expertise in generative AI or LLMs.
Proficiency in Python and experience with frameworks such as Transformers (HuggingFace), LangChain, PyTorch, or TensorFlow.
Strong understanding of NLP, deep learning, and transformer architectures.
Experience building scalable ML pipelines and deploying models to production (Docker, Kubernetes, etc.).
Familiarity with prompt engineering, fine-tuning, and model evaluation techniques.