Staff Machine Learning Engineer

September 27

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Description

• Help transform fashion retail with AI. • Match users to an amazing look by building search and recommendations. • Partner with data science, engineering, and product teams. • Build, deploy, and optimize production-ready ML systems. • Innovate unparalleled fashion search and computer vision techniques. • Develop and maintain robust data pipelines for ML models. • Monitor model performance and develop automated retraining pipelines. • Collaborate to deliver innovative AI/ML product experiences.

Requirements

• Advanced degree in Computer Science, Information Retrieval, Machine Learning, or a related field • 5+ years of experience in machine learning engineering or similar roles • Strong systems and backend engineering skills, including service design, testing, deployment, and monitoring; Kubernetes experience is a plus • Strong programming skills in Python; familiarity with other languages is a plus • Proficiency in working with large datasets and distributed computing systems • Proficiency in cloud platforms (e.g., AWS, GCP, Azure) for ML model deployment • Experience with ML model serving technologies (e.g., TensorFlow Serving, ONNX) • Solid understanding of machine learning algorithms, deep learning, and statistical modeling • Extensive experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn • Experience with natural language processing (NLP) for applications like chatbots or search • Familiarity with recommender systems and personalization algorithms • Familiarity with learning to rank, embedding, search relevance, and search relevance evaluation • Understanding of ML ops practices and tools for continuous integration and deployment of ML models

Benefits

• Competitive salary, equity and benefits (medical, dental, vision, 401k, etc.) • Flexible vacation and remote working • The opportunity to be part of a groundbreaking, AI-focused company. • Collaborative work environment with a team of talented, fun-loving individuals. • Opportunity to learn and grow in your career while shaping the future of fashion, shopping and technology