Machine Learning Intern (Masters) - Summer 2027
DoorDash · Seattle, WA · 1 mo ago
Engineering$131k–$192k/yrFull-time
We need to output HTML fragment with sections: About the team, About the role, maybe Responsibilities? The posting includes "About The Team", "About The Role", then bullet points under "You’re Excited About This Opportunity Because You Will…" and "We’re excited about you because you…". Also compensation, benefits, pay range, schedule? There's mention of 12-week summer internship program (schedule). Also mention of offices locations. Also mention of compensation details: base salary ranges, equity grants. Benefits: 401(k), parental leave, wellness, commuter benefits, PTO, sick leave, medical/dental/vision, holidays, disability, life insurance, family-forming assistance, mental health program. Also PTO details. Also mention of "Applications for this position are accepted on an ongoing basis" – that's application instruction, should be removed. Also "Talk to your recruiter for more information." – also application instruction, remove. Also "To learn more about our benefits, visit our careers page here." – remove. Also "See Below For Paid Time Off Details" – we can keep PTO details as part of benefits? Probably include in Benefits section. Also "The national base pay ranges for this position within the United States, including Illinois and Colorado." then ranges. So we need Pay section with those ranges. Also schedule: 12-week summer internship program. Also location: San Francisco, Sunnyvale, New York, or Seattle offices. Could be part of About the role or a separate Schedule? Probably schedule includes duration and location? The instruction: Use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have sections: About the team, About the role, Responsibilities? Not present. Requirements/Qualifications/Skills: we have qualifications list under "We’re excited about you because you…". Could put that as Requirements or Qualifications. Benefits: we have benefits. Pay: we have salary ranges. Schedule: we have 12-week summer internship program and locations.
We must not repeat job title as heading. No Job ID. Remove boilerplate: EEO, diversity statement, non-discrimination, scam warnings, etc. Also remove "About DoorDash" mission statement? That's maybe boilerplate but could be considered part of About the team? The posting includes "About DoorDash" after benefits. That's generic company description; could be considered boilerplate? It's not specifically about the team. Might be considered filler; but instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The "About DoorDash" paragraph is not exactly legal; it's company overview. Might be okay to keep? But it's somewhat generic. However we need to preserve ALL substantive information; not invent or summarize away detail. The "About DoorDash" is substantive about company mission. Might keep as part of About the team? But we already have About The Team section earlier. The "About DoorDash" repeats mission. Could be considered duplicated? Might be safe to keep as part of About the team? But we already have About The Team describing building logistics engine. The About DoorDash is more generic. Could be considered boilerplate? Not sure. I'd keep it as part of About the team maybe combine.
We need to output only HTML fragment, no markdown fences.
Let's structure:
headings and
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have sections: About the team, About the role, Responsibilities? Not present. Requirements/Qualifications/Skills: we have qualifications list under "We’re excited about you because you…". Could put that as Requirements or Qualifications. Benefits: we have benefits. Pay: we have salary ranges. Schedule: we have 12-week summer internship program and locations.
We must not repeat job title as heading. No Job ID. Remove boilerplate: EEO, diversity statement, non-discrimination, scam warnings, etc. Also remove "About DoorDash" mission statement? That's maybe boilerplate but could be considered part of About the team? The posting includes "About DoorDash" after benefits. That's generic company description; could be considered boilerplate? It's not specifically about the team. Might be considered filler; but instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The "About DoorDash" paragraph is not exactly legal; it's company overview. Might be okay to keep? But it's somewhat generic. However we need to preserve ALL substantive information; not invent or summarize away detail. The "About DoorDash" is substantive about company mission. Might keep as part of About the team? But we already have About The Team section earlier. The "About DoorDash" repeats mission. Could be considered duplicated? Might be safe to keep as part of About the team? But we already have About The Team describing building logistics engine. The About DoorDash is more generic. Could be considered boilerplate? Not sure. I'd keep it as part of About the team maybe combine.
We need to output only HTML fragment, no markdown fences.
Let's structure:
About the Team
DoorDash is building the world’s most reliable on-demand logistics engine for delivery.
About the Role
As a Machine Learning Engineer intern at DoorDash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across DoorDash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices.
Maybe schedule separate: but we already mentioned schedule in About the role. Could still have Schedule section with details: 12-week summer internship program, locations. But instruction: prefer a few substantive sections over many thin ones. So we could combine About the role and Schedule into one? But they ask to use headings for Schedule if present. Since we have schedule info, we could make a Schedule section. Let's decide: Have About the team, About the role, Responsibilities? Not present. Requirements/Qualifications/Skills: we have qualifications list. Benefits: we have benefits. Pay: we have salary ranges. Schedule: we have internship duration and locations. Thus sections: About the team, About the role, Qualifications, Benefits, Pay, Schedule. Now extract content. About the team: "DoorDash is building the world’s most reliable on-demand logistics engine for delivery!" Could also include mission? But we keep short. About the role: As a Machine Learning Engineer intern at DoorDash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across DoorDash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. But schedule will be separate; maybe we move the schedule info to Schedule section and keep About the role without schedule. Thus About the role: As a Machine Learning Engineer intern at DoorDash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across DoorDash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. Qualifications/Skills: "We’re excited about you because you…" list: - Are working towards a Masters degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 - Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) - Have experience in research and in solving analytical problems - Are a strong communicator and team player. - Have a passion for applied ML and the Doordash product - Ideally have worked on publications in machine learning, AI, data science, data analytics, statistics, or related technical fields Also earlier: "You’re Excited About This Opportunity Because You Will…" list: - Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads, forecasting, fulfillment and search experiences at Doordash. - Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. - Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. - Write clean, efficient, and sustainable code These could be Responsibilities. So we can have Responsibilities section with those bullet points. Thus sections: About the team, About the role, Responsibilities, Qualifications, Benefits, Pay, Schedule. Now Benefits: list: - 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) - medical, dental, and vision benefits - 11 paid holidays - disability and basic life insurance - family-forming assistance - mental health program - PTO 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). Also equity grants mentioned in compensation. Pay: Base salary ranges: I4 $130,600—$192,000 USD; I5 $159,800—$235,000 USD; I6 $193,800—$285,000 USD. Also mention equity grants. Schedule: 12-week summer internship program in San Francisco, Sunnyvale, New York, or Seattle offices. Now we need to output HTML with headings and - for lists,
for prose.
We must not include application instructions like "Applications for this position are accepted on an ongoing basis", "Talk to your recruiter for more information.", "To learn more about our benefits, visit our careers page here.", "See Below For Paid Time Off Details". Also remove EEO, diversity statement, non-discrimination, scam warnings, etc. Also remove "About DoorDash" mission paragraph? Might be considered boilerplate but it's not legal; but it's generic company description. Could be considered part of About the team? We already have About the team short. The longer About DoorDash could be considered duplicate? I'd omit it to avoid boilerplate.
Also remove "Compensation" heading? We'll use Pay section.
Now craft HTML.
We need to ensure we don't include any markdown fences.
Let's produce:
About the Team
DoorDash is building the world’s most reliable on-demand logistics engine for delivery.
About the Role
As a Machine Learning Engineer intern at DoorDash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across DoorDash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics.
Responsibilities
- Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads, forecasting, fulfillment and search experiences at DoorDash.
- Contribute and execute on research ideas that can be applied and used to improve product experience at DoorDash.
- Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models.
- Write clean, efficient, and sustainable code.
Qualifications
- Working towards a Masters degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and graduating between Fall 2027 & Summer 2028.
- Mastery of at least one systems language (Java, C++, Python, Kotlin, GoLang) or one ML framework (TensorFlow, PyTorch, MLFlow).
- Experience in research and solving analytical problems.
- Strong communicator and team player.
- Passion for applied ML and the DoorDash product.
- Ideally, have worked on publications in machine learning, AI, data science, data analytics, statistics, or related technical fields.
for prose. We must not include application instructions like "Applications for this position are accepted on an ongoing basis", "Talk to your recruiter for more information.", "To learn more about our benefits, visit our careers page here.", "See Below For Paid Time Off Details". Also remove EEO, diversity statement, non-discrimination, scam warnings, etc. Also remove "About DoorDash" mission paragraph? Might be considered boilerplate but it's not legal; but it's generic company description. Could be considered part of About the team? We already have About the team short. The longer About DoorDash could be considered duplicate? I'd omit it to avoid boilerplate. Also remove "Compensation" heading? We'll use Pay section. Now craft HTML. We need to ensure we don't include any markdown fences. Let's produce:
About the Team
DoorDash is building the world’s most reliable on-demand logistics engine for delivery.
About the Role
As a Machine Learning Engineer intern at DoorDash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across DoorDash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics.
Responsibilities
- Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads, forecasting, fulfillment and search experiences at DoorDash.
- Contribute and execute on research ideas that can be applied and used to improve product experience at DoorDash.
- Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models.
- Write clean, efficient, and sustainable code.
Qualifications
- Working towards a Masters degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and graduating between Fall 2027 & Summer 2028.
- Mastery of at least one systems language (Java, C++, Python, Kotlin, GoLang) or one ML framework (TensorFlow, PyTorch, MLFlow).
- Experience in research and solving analytical problems.
- Strong communicator and team player.
- Passion for applied ML and the DoorDash product.
- Ideally, have worked on publications in machine learning, AI, data science, data analytics, statistics, or related technical fields.