Description

You will design, build, and deploy generative AI models and LLM-powered features for production systems, owning the full lifecycle from prompt engineering to infrastructure scaling.

This role is hybrid.

Responsibilities

• Build and fine-tune LLMs and generative models for text, image, and multimodal applications.
• Architect and implement AI-driven features, ensuring scalability and reliability in production.
• Optimize prompts and integrate retrieval-augmented generation (RAG) to maximize model performance.
• Explore emerging GenAI techniques like diffusion models and apply them to solve business challenges.
• Mentor junior engineers and collaborate with product and data teams to deliver AI solutions.

Required Skills

• 5+ years of AI/ML development experience, including 2+ years focused on Generative and Agentic AI.
• Strong proficiency in Python with PyTorch, TensorFlow, and Hugging Face Transformers.
• Hands-on experience with LLMs (GPT, LLaMA, Claude) and fine-tuning techniques.
• Expertise in NLP, generative modeling, and multimodal AI.
• Experience with vector databases (Pinecone, FAISS) and embeddings.
• Proficiency with cloud platforms (AWS, Azure, GCP) and MLOps tools (MLflow, Docker, Kubernetes).
• Strong knowledge of data structures, algorithms, and distributed systems.
• Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.

Preferred Skills

• Experience with multimodal AI, diffusion models, and reinforcement learning with human feedback (RLHF).
• Contributions to open-source GenAI projects or a strong publication record.

Key Skills

Education

Bachelor's or Master's degrees