Staff Software Engineer, Machine Learning Infrastructure
DoorDashAbout the role
About the Team
Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on talented engineers to help us create and maintain a 24x7, no downtime, global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers.
About the Role
At DoorDash, our Data Scientists have the opportunity to dive into a wealth of delivery data to improve company-wide ML workflows such as Search & Recommendations, Dasher Assignment, ETA Prediction, and Dasher Capacity Planning. You will join a small team to build systems that empower efficient machine learning at scale. This is a hybrid opportunity in San Francisco, Sunnyvale, Seattle, or New York.
You’re excited about this opportunity because you will…
- Build a world-class ML platform where models are developed, trained, and deployed seamlessly
- Work closely with Data Scientists and Product Engineers to evolve the ML platform as per their use cases
- You will help build high performance and flexible pipelines that can rapidly evolve to handle new technologies, techniques and modeling approaches
- You will work on infrastructure designs and solutions to store trillions of feature values and power hundreds of billions of predictions a day
- You will help design and drive directions for the centralized machine learning platform that powers all of DoorDash's business
- Improve the reliability, scalability, and observability of our training and inference infrastructure
We’re excited about you because…
- B.S., M.S., or PhD. in Computer Science or equivalent
- Exceptionally strong knowledge of CS fundamental concepts and OOP languages
- 8+ years of industry experience in software engineering
- Have at least 1 year of Technical Lead experience
- Prior experience building machine learning systems in production such as enabling data analytics at scale
- Prior experience in machine learning - you've developed and deployed your own models - even if these are simple proof of concepts
- Systems Engineering - you've built meaningful pieces of infrastructure in a cloud computing environment. Bonus if those were data processing systems or distributed systems
Nice To Haves
- Experience with challenges in real-time computing
- Experience with large scale distributed systems, data processing pipelines and machine learning training and serving infrastructure
- Experience with Pandas and Python machine learning libraries and deep learning frameworks such as PyTorch and TensorFlow
- Experience with Spark, MLLib, Databricks,MLFlow, Apache Airflow, Dagster and similar related technologies.
- Experience with large language models like GPT, LLAMA, BERT, or Transformer-based architectures
- Experience with fine-tuning and optimizing LLM’s
- Familiar with a cloud based environment such as AWS
- Experience in distributed model training with GPU’s
About DoorDash
At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods.
DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.
Our Commitment to Diversity and Inclusion
We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.
Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categorie
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