About Fegmo
Fegmo is building the future of AI-powered video commerce. We enable users to discover, engage with, and purchase products through interactive video experiences powered by Generative AI, multimodal intelligence, recommendation systems, and AI agents.
We are looking for exceptional AI engineers who are passionate about building production-grade AI systems and solving challenging problems at the intersection of AI, video, and commerce.
Role Overview
As an AI Engineer, you will design, develop, and deploy AI-powered products that enhance content understanding, personalization, search, recommendations, and user engagement across our video commerce platform. You will work closely with product, engineering, and mobile teams to build scalable AI systems that directly impact business growth and customer experience.
Responsibilities
- Build and deploy production-grade AI/ML solutions for video commerce applications.
- Develop AI-powered features using Large Language Models (LLMs), multimodal models, and agentic workflows.
- Design and optimize recommendation, ranking, search, and personalization systems.
- Create solutions for video understanding, product tagging, content moderation, and metadata generation.
- Develop and maintain RAG pipelines, vector search systems, and AI agents.
- Optimize model performance, inference latency, scalability, and reliability.
- Establish evaluation frameworks and monitoring systems for AI applications.
- Collaborate with product, backend, and mobile engineering teams to integrate AI capabilities into customer-facing products.
- Stay current with advancements in Generative AI, multimodal AI, agent systems, and machine learning research.
Qualifications
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Strong academic background, preferably from a reputed engineering institution.
- Strong fundamentals in Machine Learning, Deep Learning, NLP, and Generative AI.
- Proficiency in Python and modern AI frameworks such as PyTorch or TensorFlow.
- Experience building and deploying AI systems in production environments.
- Hands-on experience with LLMs, prompt engineering, RAG, vector databases, and AI agents.
- Strong understanding of software engineering best practices, system design, and scalable architectures.
- Excellent problem-solving and communication skills.
Preferred Qualifications
- Experience with recommendation systems, search, ranking, or personalization.
- Experience with video understanding, multimodal AI, or computer vision.
- Familiarity with agent frameworks such as LangGraph, CrewAI, AutoGen, or similar.
- Experience deploying AI workloads on AWS, GCP, or Azure.
- Contributions to open-source projects, research publications, or AI competitions.
Experience Requirements
- Preferred: 5+ years of experience in AI/ML engineering, data science, or applied AI roles.
- Also Open To: Exceptional candidates with 2–3 years of relevant experience who have demonstrated strong technical depth, significant hands-on AI/ML experience, and a track record of delivering impactful AI solutions.
What We Look For
- Strong ownership mindset and the ability to thrive in a startup environment.
- Passion for building AI-native products from the ground up.
- Ability to translate complex business problems into scalable AI solutions.
- Persistent curiosity to experiment with cutting-edge AI technologies and rapidly ship impactful features.
Tech Stack
- Languages & Frameworks: Python, PyTorch, TensorFlow
- AI & Architecture: LLMs & Generative AI, Multimodal AI, Video Understanding & Computer Vision
- Data & Agents: RAG & Vector Databases, LangGraph / Agent Frameworks
- Systems: Recommendation Systems, AWS / GCP