Software Engineer, Machine Learning Platform - MDX

Aimlroles; San Francisco (CA); Ibrido; USD 131.000 - 192.000; Tempo pieno

Descrizione del lavoro

DoorDash is seeking skilled data scientists and ML engineers to advance our on-demand logistics platform. You will build scalable ML systems for Search, Recommendations, ETA prediction, and Dasher capacity planning in a hybrid setup across San Francisco, Sunnyvale, or Seattle.

You'll collaborate with data scientists and product engineers, deploy models to production, and help design high-performance data pipelines and infrastructure powering trillions of feature values and billions of

Competenze

• BS/MS/PhD in CS or equivalent.
• Strong CS fundamentals and OOP knowledge.
• 2+ years of industry software engineering experience.
• Prior experience building ML systems in production.
• Experience deploying ML models to production environments.

Mansioni

• Build a world-class ML platform for model training, deployment, and inference.
• Collaborate with Data Scientists and Product Engineers to evolve the ML platform.
• Develop high-performance pipelines capable of handling large-scale data.
• Design infrastructure to store trillions of feature values and support billions of predictions daily.
• Drive directions for centralized ML platform powering DoorDash's business.

Conoscenze

CS fundamentals

OOP languages

Software engineering

ML systems in production

Model deployment

Cloud infrastructure

Formazione

B.S./M.S./PhD in Computer Science or equivalent

Strumenti

Pandas

Python ML libraries

PyTorch

TensorFlow

Spark

MLLib

Databricks

MLFlow

Airflow

Dagster

AWS

Descrizione del lavoro

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 and ML Engineers 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 or Seattle.

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
• 2+ years of industry experience in software engineering
• 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
• Familiar with Pandas and Python machine learning libraries and deep learning frameworks such as PyTorch and TensorFlow
• Familiar with Spark, MLLib, Databricks,MLFlow, Apache Airflow, Dagster and similar related technologies.
• Familiar with large language models like GPT, LLAMA, BERT, or Transformer-based architectures
• Familiar with a cloud based environment such as AWS

Compensation

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 future.

In addition to base salary, the compensation for this role includes opportunities for equity grants.

DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.

See below for paid time off details:

• For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
• For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).

The national base pay range for this position within the United States, including Illinois and Colorado.$130,600—$192,000 USD

About DoorDash

We are a technology and logistics company that started by enabling door-to-door delivery, and we are looking for team members who can help us go from a company that is known as the place you order 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 categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination.

Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.

If you need any accommodations, please inform your recruiting contact upon initial connection.