We’re looking for a Senior AI Engineer — a hands-on technical leader with deep expertise in AI/ML, large-scale data engineering, and modern GenAI workflows. You thrive in high-autonomy, fast-moving environments, combining strong research skills with the ability to ship production-ready systems. This is a high-ownership role for someone who pairs technical excellence with a product mindset, mentors others, and solves complex problems in real time. Key Responsibilities 1. Lead AI Research & Model Development Lead AI research and development, designing and implementing state-of-the-art machine learning and deep learning models. Develop cutting-edge AI algorithms for NLP, computer vision, generative AI, and bias detection. Optimize deep learning architectures (transformers, CNNs, RNNs, diffusion models) for accuracy, efficiency, and cost-effective inference. Apply advanced mathematical concepts (linear algebra, probability, discrete mathematics, statistics, optimization) to AI model development. 2. Build & Deploy GenAI Solutions Build and deploy Python-based GenAI solutions for analyzing and improving ad content. Work with large-scale, complex datasets — from acquisition to preprocessing, feature engineering, and augmentation — to enable high-quality model training and evaluation. Design and implement LLM-based pipelines using tools like LangChain, LlamaIndex, and OpenAI APIs. Own development of RAG systems, vector search, and prompt workflows. 3. Production-Ready AI Systems Build robust APIs to integrate AI models into production systems (FastAPI, Flask, Django). Design scalable AI solutions with MLOps best practices for production-ready deployment. Move fast: ship features, not just prototypes. Required Skills & Experience 1. Core AI/ML Expertise 5+ years of experience in Python and AI/ML engineering. Strong understanding of LLM-based workflows, embeddings, prompt engineering, and RAG. Experience with modern GenAI frameworks (e.g., LangChain, LlamaIndex). Experience working with large-scale datasets, preprocessing, feature engineering, and augmentation. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate). 2. Software Engineering & Deployment Ability to build and deploy APIs using FastAPI, Flask, or equivalent. Solid software engineering habits: clean code, version control, CI/CD. Cloud computing expertise (AWS, GCP, Azure) for scalable AI deployments. Experience with LLM cost optimization and open-source model deployment. 3. Leadership & Collaboration Mentoring and guiding AI engineers, fostering a research-driven development culture. Why Join us? Work on large-scale AI projects with real-world impact High autonomy, high-impact role on a lean, ambitious team Shape both the product and technical foundation of AI systems Fully remote work with flexibility Competitive compensation and opportunities for career growth. Continuous learning, experimentation, and exposure to cutting-edge AI tools Originally posted on Himalayas