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Mid-level generative AI role with niche LLM skills but non-Tier1 employer increases moderate competition.
Strong ML/AI domain specialization (LLMs, prompt engineering, vector search) makes background highly specific.
Explicit 5–8 years plus mandatory LLM, PyTorch/HuggingFace, vector DB, cloud, Docker/Kubernetes, and MLOps requirements.
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Lead design, development, and deployment of scalable Generative AI solutions including LLM-powered applications and AI pipelines.
Manage full AI model lifecycle: data preprocessing, training, fine-tuning, deployment, monitoring, and optimization for performance and cost.
Mentor junior engineers and collaborate cross-functionally to integrate AI into products and workflows.
Bachelor’s or Master’s degree in Computer Science, AI, ML, Data Science, or related field.
5–8 years of experience in AI/ML model development and deployment.
Proficiency with Generative AI, Large Language Models (LLMs), Python, and AI frameworks like PyTorch, TensorFlow, Hugging Face Transformers.
Experience with cloud platforms (AWS, GCP, Azure), vector databases (Pinecone, Weaviate, ChromaDB, FAISS), containerization (Docker, Kubernetes), and MLOps practices.
Experienced in leading technical AI projects and mentoring teams in Generative AI/LLM domains.
Operates well in fast-paced, innovative environments requiring cross-functional collaboration and strategic AI integration.
Strong hands-on expertise in practical deployment, fine-tuning, and optimization of large-scale AI models and infrastructure.