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 of the following languages: Go, Java, C++ for production
systems and Python for data analysis and offline pipelines.
* Demonstrated ability to translate mathematical formulations into production
code that runs at scale (millions of decisions per day, sub-100ms latency
constraints).
PREFERRED QUALIFICATIONS
* Experience with real-time bidding systems, ad auction optimization, or
computational advertising at scale.
* Background in budget-constrained allocation methods. Experience with adaptive
control or model-predictive control in production systems.
* Familiarity with causal inference and experimental design for evaluating
algorithmic changes in marketplace settings.
* Track record of shaping technical strategy and driving cross-functional
alignment between engineering, product, and data science.
Instacart provides highly market-competitive compensation and benefits in each
location where our employees work. This role is remote and the base pay range
for a successful candidate is dependent on their permanent work location. Please
review our Flex First remote work policy here
[
Offers may vary based on many factors, such as candidate experience and skills
required for the role. Additionally, this role is eligible for a new hire equity
grant as well as annual refresh grants. Please read more about our benefits
offerings here [
For US based candidates, the base pay ranges for a successful candidate are
listed below.
CA, NY, CT, NJ
$240,000—$253,500 USD
WA
$230,000—$243,000 USD
OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI
$221,000—$233,000 USD
All other states
$201,000—$212,000 USD
