AI / Generative AI Engineer (Remote)

Requirements

About the Role:

AI / Generative AI Engineer

Key Responsibilities:

• Design, develop, and deploy Generative AI models (LLMs, diffusion models, transformers) for real-world applications.
• Fine-tune foundation models using proprietary or domain-specific datasets.
• Integrate LLMs and generative models into production pipelines, APIs, and applications.
• Conduct research and experimentation on prompt engineering, model alignment, and retrieval-augmented generation (RAG).
• Collaborate with cross-functional teams including product managers, data scientists, and software engineers.
• Evaluate model performance and optimize for latency, accuracy, and ethical use.
• Stay updated with the latest in GenAI research (e.g., OpenAI, Hugging Face, Meta, Google DeepMind) and bring best practices to the team.
  

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, Data Science, or a related field.
• 3+ years of experience in machine learning, with at least 1–2 years focused on Generative AI or NLP.
• Proficiency in Python and libraries like PyTorch, TensorFlow, Hugging Face Transformers, LangChain, or OpenAI API.
• Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude), image generation models (e.g., Stable Diffusion), or speech models (e.g., Whisper).
• Strong understanding of deep learning architectures (RNNs, CNNs, transformers).
• Experience with MLOps, model serving (e.g., Triton, FastAPI), and scalable cloud deployment (AWS, GCP, Azure).
• Familiarity with prompt engineering and fine-tuning techniques (LoRA, PEFT, RLHF).
  

Desirable:

• Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and RAG pipelines.
• Knowledge of ethical AI principles, bias mitigation, and responsible AI practices.
• Contributions to open-source projects or published research in AI/ML conferences or journals.
• Experience working with multi-modal models (text+image+audio).