Software Engineer, Machine Learning - Fraud
$137.1k - $201.6kDoordash Usa
About the Team
The Fraud Machine Learning team builds cutting edge models that play central roles in our important anti-fraud systems. We operate at a massive scale, risking billions of events across 20+ countries. We are looking for ML experts who can help us push the technology boundaries and make DoorDash the world’s most safe logistics engine!
About the Role
We’re looking for a passionate Applied Machine Learning engineer to join our team. As a Machine Learning Engineer, you’ll be conceptualizing, designing, implementing, and validating algorithmic solutions to prevent, detect and mitigate fraud. You are excited about opportunities to introduce step function changes to our risking system. You will demonstrate a command of production level machine learning, experience solving end-user problems, and collaborate well with multi-disciplinary teams.
You will report into the engineering manager on our Fraud Machine Learning team in our Operation Excellence organization. Once our offices reopen, we expect this role to be hybrid with some time in-office and some time remote.
You're excited about this opportunity because you will...
- Develop production machine learning solutions to build a safe and frictionless 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
We're excited about you because you have...
- 2+ years of industry experience developing machine learning models ( both classical and deep learning) and shipping ML solutions to production.
- Experience with PyTorch or TensorFlow or similar deep learning framework.
- M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Bioinformatics, Economics, or other quantitative fields
- Familiarity with a JVM language (Kotlin/Scala)
- Familiarity with multi-task learning, LLMs and anomaly detection
- Fraud domain knowledge
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 from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for 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
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 .
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 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.
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...experienced Field Applications Engineer to be a key technical... ...AI, processor, sensor, and software solutions. The ideal candidate... ...~ Experience with edge AI, machine learning deployment, low-power... ...Legal Support, and Identity Fraud Protection. About Syntiant...FraudTemporary workFlexible hours- ...looking for a full stack backend engineer, who will be working... ...be founding members of a new Fraud Engineering team at Sidecar.... ...coupled with experience around machine learning, pattern recognition, etc.... ...Passion for finding problems with software and helping ensure they...FraudWork at office
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...seeking an experienced Sr. Associate, Software Engineer to join our dynamic team. In this role,... ...initiatives including credit scoring, fraud detection, and customer segmentation. Delivery... ..., and fostering a culture of learning and continuous improvement. Data Modeling...FraudFull timeInternshipWork at office$293k - $385k
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