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Senior Software Engineer, Machine Learning - Consumer ML Job Opening In San Francisco – Now Hiring DoorDash


Job description

About the Team
Come help us build the world's most reliable on-demand, logistics engine for last-mile retail delivery! We're looking for an experienced machine learning engineer to help us develop modern growth and personalization models that power DoorDash's growing retail and grocery business.
About the Role
We’re looking for a passionate Applied Machine Learning expert to join our team.

As a Senior Machine Learning Engineer, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the growth and personalization experiences 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 the consumer search experience more relevant, seamless, and delightful across grocery, convenience, and many other retail categories.

You will demonstrate a strong command of production level machine learning, experience with solving end-user problems, and collaborate well with multi-disciplinary teams.

You will report into the engineering manager on our Personalization team.

We expect this role to be hybrid with some time in-office and some time remote (#LI-Hybrid).
You’re excited about this opportunity because you will…

+ Develop production machine learning solutions to build a world class personalized shopping experience for a diverse and expanding retail space

+ Partner with engineering and product leaders to help shape the product roadmap applying ML

+ Mentor junior team members, and lead cross functional pods to create collective impact


You can find out more on our ML blog here (https://doordash.engineering/category/data-science-and-machine-learning/)
We’re excited about you because you have…

+ 5+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production.



+ M.S., or PhD.

in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field

+ Expertise in applied ML for Causal Inference and Recommendation Systems - both classical and deep learning based.

Additional familiarity with explore/exploit/MAB algorithms & LLMs is a plus.



+ Machine learning background in Python; experience with PyTorch or TensorFlow preferred.

+ Ability to communicate technical details to nontechnical stakeholders

+ You keep the mission in mind, take ideas and help them grow using data and rigorous testing, show evidence of progress and then double down

+ Desire for impact with a growth-minded and collaborative mindset




Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC.

As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications.

We began using Covey Scout for Inbound (https://getcovey.com/product/covey-scout-inbound) from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound (https://getcovey.com/product/covey-scout-inbound) again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor.

Results of the audit may be viewed here: Covey (https://getcovey.com/nyc-local-law-144)


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.

Talk to your recruiter for more information.

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.

To learn more about our benefits, visit our careers page here (https://careers.doordash.com/) .

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 ranges for this position within the United States, including Illinois and Colorado.

I4

$137,100 — $201,600 USD


I5

$167,800 — $246,800 USD


I6

$203,500 — $299,300 USD


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 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.


Required Skill Profession

Other General


  • Job Details

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at DoorDash adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying United States laws and regulations

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The average salary range for a varies, but the pay scale is rated "Standard" in San Francisco. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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Key qualifications for Senior Software Engineer, Machine Learning Consumer ML typically include Other General and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for Senior Software Engineer, Machine Learning Consumer ML Job Success

DoorDash interview tips for Senior Software Engineer, Machine Learning   Consumer ML

Here are some tips to help you prepare for and ace your Senior Software Engineer, Machine Learning Consumer ML job interview:

Before the Interview:

Research: Learn about the DoorDash's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Senior Software Engineer, Machine Learning Consumer ML interview at DoorDash, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the DoorDash's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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