Machine Learning Engineer, Computer Vision

Machine Learning Engineer, Computer Vision

Door Dash | Posted Feb 26, 2026

Full-time

Negotiable

Entry (0-2 yrs)

Come help us build the world's most reliable on-demand, logistics engine for last-mile grocery and retail delivery! We're looking for an experienced senior machine learning engineer to help us develop the cutting-edge Computer Vision models that power Door Dash's growing grocery and retail business.

We’re looking for a passionate Applied Machine Learning expert to join our team. As a Computer Vision expert, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the computer vision system at the heart of our fast-growing grocery and retail delivery business. You will use our robust data and machine learning infrastructure to implement new ML solutions to make our product knowledge graph and inventory information more accurate and real time, as well as help Dasher efficiency.

We’re looking for someone with a command of production-level machine learning and experience with solving end‑user problems who enjoys collaborating with multidisciplinary teams.

• Develop production machine learning solutions to solve consumer vision problems such as entity recognition, entity resolution, attribute extraction, object detection, segmentation, metric learning, and category classification, image classification.
• Collaborate with cross‑functional leaders across engineering, product, and business strategy to help shape a product roadmap driven by machine learning, accelerating the growth of a multi‑billion‑dollar retail delivery ecosystem.
• Explore and harness diverse data sources, leveraging intuitive models and fostering a culture of flexible experimentation. Your goal will be to continuously improve the shopping and dashing experiences, delivering solutions that are not only effective but also scalable and user‑centric.
• Drive impact and enjoy ample room for both personal and professional growth. This includes opportunities for deep technical development and leadership as you work within a growing team that is actively unlocking new markets for the company.
• Innovate and experiment with cutting‑edge technologies and methodologies in AI and ML. You’ll have the freedom to explore emerging technologies, test new ideas, and drive technical innovation in the computer vision space, directly shaping the future of our retail and delivery solutions.

• 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, Tensor Flow, or Spark. You’re able to implement scalable models and optimize performance for production systems.
• You must be located near one of our engineering hubs which includes:
  San Francisco, Sunnyvale, Los Angeles, Seattle, and New York.
• M.S., or Ph.D. 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.

The successful candidate's starting pay will fall within the pay range listed below and is determined based on job‑related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market‑dependent and may be modified in the…