AI Engineer

Summary

Join fabric, a next-generation commerce platform revolutionizing the industry, as an AI Engineer. You will be part of a small, high-impact team designing, building, and scaling an agentic AI platform. This role involves contributing to end-to-end AI/ML solutions, developing production-grade pipelines, and applying various AI/ML techniques. You will also help build intelligent data products and support MLOps efforts. Collaboration with cross-functional teams is key. This is a 0-1 environment offering the chance to shape the AI foundation of a well-funded startup.

Requirements

• 5+ years of experience in applied ML/AI roles, ideally within product-focused environments or high-growth startups
• Proven experience building and deploying ML models for real-world use cases (e.g., recommendations, search, NLP, categorization)
• Data Engineering (feature engineering/ store, distributed data processing)
• Modeling (deep learning, classical ML, RL, unsupervised learning)
• MLOps (deployment, monitoring, CI/CD, infrastructure). Product Building - building end-end SAAS products
• Strong programming skills using Spark, Python, TensorFlow/PyTorch, MLFlow, Airflow, Docker, Kubernetes, etc
• Bachelor’s or Master’s degree in Computer Science, Engineering, Econometrics/ Statistics, or related field—or equivalent practical experience
• Passion for building usable, scalable products — not just research or models
• Clear communicator with a collaborative mindset, eager to grow and contribute within a small, fast-paced team

Responsibilities

• Contribute to end-to-end AI/ML solutions: Help frame problems, design models, train, evaluate, and deploy AI/ML systems into production
• Develop production-grade pipelines: Implement pipelines for model training, testing, serving, and monitoring
• Apply a variety of AI/ML techniques: From classical supervised/unsupervised learning to deep learning and optimization techniques, depending on the problem at hand
• Help build intelligent data products: Such as recommendation engines, personalization, categorization, search ranking, forecasting, and fraud detection
• Support MLOps efforts: Participate in maintaining infrastructure and tooling to support rapid experimentation and reliable deployment
• Collaborate across teams: Work closely with product managers, designers, and software engineers to build AI agents that solve real world problems
• Stay curious and informed: Explore new tools, libraries, and research to keep improving the quality and performance of our AI systems

Preferred Qualifications

Experience with Knowledge graphs is a big plus

Benefits

• Competitive compensation packages
• PTO and Holiday plans
• Benefits packages which include Medical, Dental, Life, and Vision
• Wellness & Technology Programs
• Retirement Savings Plan