AI Engineer SR (CHR/AI-20250812)

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