Jobs / United States / Maplebear INC D/b/a Instacart
Senior Applied Scientist II, Ads Optimization
Maplebear INC D/b/a Instacart · 🇺🇸 United States - Remote · Remote
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordUSCIS Data Hub records 42 H-1B approvals for this employer in FY2023. Source: USCIS H-1B Employer Data Hub (US Citizenship and Immigration Services).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Maplebear INC D/b/a Instacart
USCIS Data Hub records 42 H-1B approvals for this employer in FY2023. Source: USCIS H-1B Employer Data Hub (US Citizenship and Immigration Services).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Maplebear INC D/b/a Instacart →
About the role
We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Advertiser Optimization team is the decision-making engine of Instacart's $1B+ ads business. We own the systems responsible for Bidding, Pacing, Budgeting, and Targeting: converting stated advertiser goals into real-time auction actions. Our mission is to maximize realized Advertiser Value by deciding when to participate, how much to bid, and how fast to spend, all while balancing User Experience and Platform Revenue. We are hiring a Senior Applied Scientist II to lead the algorithmic direction of these systems. This is a role for someone who thinks in terms of control theory, constrained optimization, and auction economics, and who can translate those frameworks into production code that makes millions of decisions per day. You will formulate problems from first principles, shape the technical roadmap, and own systems end-to-end from mathematical design through production deployment through impact measurement. About the Job • Design and evolve real-time bid optimization systems that translate advertiser goals (target ROAS, budget constraints) into optimal auction bids under uncertainty. Formulate the bidding problem as constrained optimization and build the feedback mechanisms that keep bids aligned with realized outcomes. • Build intelligent budget pacing algorithms that distribute spend across time and auction opportunities. The core challenge: allocating a finite daily budget across stochastic demand while maximizing total value, subject to advertiser constraints and time-varying conversion dynamics. • Develop the analytical frameworks that connect bidding, pacing, and budgeting into a coherent optimization objective. • Shape auction mechanics including reserve pricing, multi-slot allocation, and bid-to-price mapping. Reason about mechanism design tradeoffs between advertiser outcomes, platform revenue, and marketplace efficiency. • Own the full research-to-production loop: diagnose system behavior from large-scale data, formulate hypotheses, design experiments, ship production code, and measure impact. Write technical strategy documents that set the algorithmic direction for the team. About You Minimum Qualifications • Graduate degree (Masters or PhD) in operations research, applied mathematics, control systems, computational economics, or a related quantitative field. • 8+ years of experience building and deploying optimization or control systems in production environments (not just research prototypes). • Strong foundation in at least two of: feedback control theory (PID, MPC), convex and stochastic optimization, auction theory and mechanism design, dynamic programming. • Proficiency in one