Job Title: Machine Learning Engineer, Computer Vision
Our mission is to empower local economies through logistics and technology. We're seeking an experienced senior machine learning engineer to help develop cutting-edge Computer Vision models for our grocery and retail delivery business.
Key Responsibilities
• Develop production machine learning solutions for computer vision problems such as entity recognition, entity resolution, attribute extraction, object detection, segmentation, metric learning, and category classification.
• Collaborate with cross-functional leaders to shape a product roadmap driven by machine learning and accelerate the growth of our multi-billion-dollar retail delivery ecosystem.
• Explore diverse data sources, leverage intuitive models, and foster a culture of flexible experimentation. Your goal will be to continuously improve the shopping and dashing experiences, delivering solutions that are effective, scalable, and user-centric.
• Drive impact and enjoy opportunities for personal and professional growth, including deep technical development and leadership within a growing team that unlocks new markets for the company.
• Innovate and experiment with cutting-edge technologies and methodologies in AI and ML, directly shaping the future of our retail and delivery solutions.
Requirements
• Industry experience developing machine learning models with business impact and shipping ML solutions to production. You have successfully shipped ML solutions to production and understand the nuances of transitioning models from development to real-world environments.
• Deep expertise in applied Computer Vision, with hands-on experience solving challenging vision-related problems and implementing solutions that drive customer value. Your knowledge extends to solving complex tasks such as object detection, classification, and segmentation.
• Strong machine learning and programming skills, particularly in Python, with experience in key ML frameworks such as PyTorch, TensorFlow, or Spark. You're able to implement scalable models and optimize performance for production systems.
• Location flexibility near one of our engineering hubs, which includes San Francisco, Sunnyvale, Los Angeles, Seattle, and New York.
• M.S., or PhD. in Computer Vision, Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field is a plus.
• Familiarity with causal inference and experimentation techniques, enabling you to design and evaluate experiments that validate the effectiveness of ML models and ensure the product's continuous improvement.
