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Senior Technical Program Manager, Caper Machine Learning

Instacart

Senior Technical Program Manager, Caper Machine Learning

Instacart

USA - Remote

·

Remote

·

Full-time

·

1mo ago

Compensation

$178,000 - $226,000

Benefits & Perks

Flexible PTO policy

Learning and development stipend

Annual team offsites

Health, dental, and vision coverage

Top Tier compensation with equity

Required Skills

SQL

Airflow

Python

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

Caper, an Instacart team building AI-powered checkout experiences, is on the cutting edge of physical AI—bringing computer vision and on-device machine learning to the real world through smart carts and connected retail hardware.

We are seeking a Senior Technical Program Manager to lead complex, multi-quarter machine learning & computer vision engineering programs that power the heart of Caper: high-quality data pipelines, robust model training and evaluation, and reliable on-cart deployment at scale. You will partner closely with computer vision and machine learning engineers, Android engineers, hardware teams, product, operations, and the executive team to build the roadmap, drive execution, and deliver measurable improvements to model performance and in-store outcomes.

This role is ideal for a builder who thrives in a fast-paced, evolving environment and enjoys rolling up their sleeves to turn complex, cross-functional work into predictable delivery. Remote-friendly across the US and Canada, with a preference for West Coast time zones to maximize collaboration with our partners.

About the Job

  • Own end-to-end execution of ML programs across data collection, labeling, training, evaluation, and on-device deployment—defining scope, milestones, risks, and success metrics tied to accuracy, latency, and in-store experience.

  • Build and maintain cross-functional plans with computer vision/ML, Android, hardware, MLOps, data engineering, QA, and field operations; run cadences, surface tradeoffs, and drive on-time, high-quality releases.

  • Lead data operations at scale, including in-store capture, synthetic generation, and third-party annotation—setting data quality bars, SLAs, and e data using SQL and basic Python to validate assumptions and interpret model and product performance.

  • Experience coordinating cross-functional teams of 10+ stakeholders, including external vendors, with strong risk, dependency, and change management.

  • Excellent written and verbal communication skills, including executive-level reporting and decision facilitation.

  • Willingness to travel to stores, labs, and partner sites as needed (up to 15%).

Preferred Qualifications

  • Experience in retail technology, robotics, autonomous systems, or other physical AI domains.

  • Knowledge of on-device inference optimization and tooling (e.g., TensorRT, Core ML, Tensor Flow Lite) and performance tradeoffs on constrained hardware.

  • Background establishing data quality standards and managing third-party labeling vendors at scale.

  • Familiarity with privacy, security, and compliance considerations for in-store data collection (e.g., GDPR, CCPA).

  • Graduate degree in a relevant technical field.

  • Experience integrating hardware components (cameras, depth sensors, scales) and leading calibration/validation workflows.

  • Ability to create dashboards and operational telemetry for model and program health using tools like Looker, Mode, or similar.

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. Please read more about our benefits offeringshere.

For US based candidates, the base pay ranges for a successful candidate are listed below.
CA, NY, CT, NJ**$214,000**—$226,000 USDWA**$205,000**—$216,000 USDOR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI**$196,000**—$207,000 USDAll other states**$178,000**—$188,000 USD

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About Instacart

Instacart

Instacart

Public

Groceries delivered in as fast as 1 hour.

1,001-5,000

Employees

San Francisco that operates a grocery delivery

Headquarters

$39B

Valuation

Reviews

4.3

14 reviews

Work Life Balance

3.8

Compensation

4.2

Culture

2.5

Career

3.0

Management

2.3

65%

Recommend to a Friend

Pros

High compensation packages and competitive offers

Fully remote work flexibility

Good work-life balance

Cons

Executive departures and leadership instability

Major layoffs (7% of company)

Declining valuation (down 80% from peak)

Salary Ranges

2,113 data points

Mid/L4

Senior/L5

Staff/L6

Mid/L4 · Data Scientist L4

0 reports

$248,100

total / year

Base

-

Stock

-

Bonus

-

$210,885

$285,315

Interview Experience

5 interviews

Difficulty

3.6

/ 5

Duration

21-35 weeks

Offer Rate

60%

Experience

Positive 40%

Neutral 60%

Negative 0%

Interview Process

1

Application Review

2

Recruiter/Phone Screen

3

Technical/Coding Interview

4

System Design Interview

5

Behavioral Interview

6

Onsite/Final Round

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge