Technology Company
Job Description
About the Role
We’re looking for a
Generative AI Data Scientist
to design, train, and optimize AI models that power next-generation intelligent systems. You’ll work on projects involving large language models (LLMs), NLP, and multimodal data pipelines — helping turn research into production‑grade products.
Responsibilities
Develop and fine‑tune generative AI models (LLMs, diffusion, transformer‑based architectures).
Build and manage data pipelines for model training, evaluation, and continuous learning.
Design prompt engineering and retrieval‑augmented generation (RAG) frameworks.
Collaborate with engineers and product teams to deploy scalable inference APIs.
Evaluate model performance, bias, and data quality; implement monitoring systems.
Contribute to model interpretability, safety, and responsible AI practices.
Qualifications
MS or PhD in Computer Science, Machine Learning, Statistics, or related field.
3+ years of experience in ML/AI, with exposure to generative or transformer‑based models.
Strong Python skills (PyTorch, TensorFlow, Hugging Face, LangChain, etc.).
Experience with vector databases, RAG, and fine‑tuning open‑weight models (e.g., Llama, Mistral).
Familiarity with cloud ML environments (AWS Sagemaker, GCP Vertex, or Azure ML).
Excellent problem‑solving and communication skills.
Nice to Have
Experience deploying AI systems in production.
Knowledge of multimodal (text, image, audio) model training.
Contributions to open‑source AI projects or published research.
What We Offer
Competitive compensation
Flexible work environment.
Opportunity to work on frontier AI systems with real‑world impact.
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Generative AI Data Scientist
to design, train, and optimize AI models that power next-generation intelligent systems. You’ll work on projects involving large language models (LLMs), NLP, and multimodal data pipelines — helping turn research into production‑grade products.
Responsibilities
Develop and fine‑tune generative AI models (LLMs, diffusion, transformer‑based architectures).
Build and manage data pipelines for model training, evaluation, and continuous learning.
Design prompt engineering and retrieval‑augmented generation (RAG) frameworks.
Collaborate with engineers and product teams to deploy scalable inference APIs.
Evaluate model performance, bias, and data quality; implement monitoring systems.
Contribute to model interpretability, safety, and responsible AI practices.
Qualifications
MS or PhD in Computer Science, Machine Learning, Statistics, or related field.
3+ years of experience in ML/AI, with exposure to generative or transformer‑based models.
Strong Python skills (PyTorch, TensorFlow, Hugging Face, LangChain, etc.).
Experience with vector databases, RAG, and fine‑tuning open‑weight models (e.g., Llama, Mistral).
Familiarity with cloud ML environments (AWS Sagemaker, GCP Vertex, or Azure ML).
Excellent problem‑solving and communication skills.
Nice to Have
Experience deploying AI systems in production.
Knowledge of multimodal (text, image, audio) model training.
Contributions to open‑source AI projects or published research.
What We Offer
Competitive compensation
Flexible work environment.
Opportunity to work on frontier AI systems with real‑world impact.
#J-18808-Ljbffr