Staff Machine Learning Engineer, Daydream

• 5+ years of experience in machine learning engineering or similar roles
• Able to solve hard problems independently, while meshing with a team to accomplish shared goals
• 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)
• Willingness to learn Go, Typescript, or whatever programming language is needed to do the job
• Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes)
• 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
• Experience with image understanding models, and use in applications
• Experience in deploying ML models to production environments
• Understanding of ML ops practices and tools for continuous integration and deployment of ML models
• Experiencing improving AI/ML product features through the use of data, feedback, and analysis

Desirable

• As a Machine Learning Engineer at Daydream, you will help transform fashion retail with AI
• This role requires a unique blend of strong software engineering skills, deep machine learning expertise, and an intense focus on delivering a great experience for the user
• You will match users to an amazing look by building industry-leading content understanding (language and vision), and conversational interfaces
• You’ll partner with product and other engineering teams to bring cutting-edge AI solutions to life
• As a startup, we need MLEs that love wearing multiple hats: some weeks you’ll be a data scientist, others a backend engineer
• Work with product to create unique and effective AI agent experiences in product
• Build, deploy, and optimize production-ready, scalable backend and ML services
• Implement ML models for various applications in fashion retail (conversational interfaces, language and image understanding)
• Automate repetitive work, and enable rapid experimentation
• Develop and maintain robust data pipelines for training and serving ML models
• Implement efficient data processing and feature engineering pipelines
• Integrate external domain-specific knowledge (fashion) from experts and other sources
• Collaborate with data engineers to ensure high-quality, reliable data inputs for ML models
• Build continuous monitoring of model performance
• Develop automated retraining pipelines to keep models up-to-date
• Troubleshoot and debug issues in production ML systems
• Work closely with the team to deliver innovative AI/ML product experiences
• Productionize ML models, and improve model architectures
• Partner with product managers to translate business requirements and user journeys into technical solutions
• Innovate unparalleled fashion search, discovery, and computer vision techniques
• Contribute to company AI research initiatives and potential patent applications
• User-centric and product-centric focus - build tech to solve real user problems