
Artificial Intelligence Developer Position
1 day ago
This exciting role involves the design, creation and deployment of generative AI solutions. You will utilize Large Language Models (LLMs) such as OpenAI, Anthropic, Mistral or open-source models like LLaMA and Falcon.
You will fine-tune and customize foundation models using domain-specific datasets and techniques to drive accurate and context-aware model responses. Developing and optimizing prompt engineering strategies to enhance model performance is also a key responsibility.
Your tasks include implementing model pipelines using Python and ML frameworks like PyTorch, Hugging Face Transformers, or LangChain, collaborating with data engineers and MLOps teams to productionalize GenAI models on cloud platforms, and ensuring robustness, scalability, and compliance of AI models in deployment environments.
Experience with finetuning models and SLM is highly desirable, as is integrating GenAI into enterprise applications via APIs or custom interfaces. Evaluating model performance using quantitative and qualitative metrics and improving outputs through iterative experimentation is also essential.
Staying up-to-date with the latest research in GenAI, foundation models, and relevant open-source tools is crucial for driving innovation and excellence in this field.
Mandatory Skill Sets:- Generative AI (LLMs, Transformers)
- Python, PyTorch, Hugging Face Transformers
- Azure/AWS/GCP cloud platforms
- LangChain or similar orchestration frameworks
- REST APIs, FastAPI, Flask
- ML pipeline tools (MLFlow, Weights & Biases)
- Git CI/CD for ML (e.g., Azure ML, SageMaker pipelines)
- RAG (Retrieval-Augmented Generation)
- Vector DBs (FAISS, Pinecone, Weaviate)
- Streamlit/Gradio for prototyping
- Docker, Kubernetes (for model deployment)
- Data preprocessing & feature engineering
- NLP libraries: spaCy, NLTK, Transformers
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