AI Engineer SR (CHR/AI-20250812)

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 Responsibilities1. Lead AI Research & Model DevelopmentLead 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 SolutionsBuild 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 SystemsBuild 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 & Experience1. Core AI/ML Expertise5+ 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 & DeploymentAbility 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 & CollaborationMentoring 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 teamShape both the product and technical foundation of AI systemsFully remote work with flexibilityCompetitive compensation and opportunities for career growth.Continuous learning, experimentation, and exposure to cutting-edge AI toolsOriginally posted on Himalayas

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