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Machine Learning Operations Research Jobs (NOW HIRING)

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Machine Learning Operations Research information

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$43.5K

$102.5K

$136K

How much do machine learning operations research jobs pay per year?

As of Jun 6, 2026, the average yearly pay for machine learning operations research in the United States is $102,462.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $116,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Operations Research professional, and why are they important?

To thrive in Machine Learning Operations Research, you need strong expertise in mathematics, statistics, machine learning algorithms, and optimization techniques, typically supported by a degree in computer science, engineering, or a related quantitative field. Proficiency in programming languages like Python or R, experience with ML frameworks (such as TensorFlow or PyTorch), and knowledge of cloud computing platforms and version control systems are commonly required. Exceptional problem-solving abilities, analytical thinking, and effective communication are critical soft skills for collaborating across interdisciplinary teams. These skills and qualifications are essential for designing robust, scalable solutions that drive data-driven decision-making and operational efficiency.

What are Machine Learning Operations Research jobs?

Machine Learning Operations Research jobs involve applying principles from operations research and machine learning to solve complex decision-making and optimization problems in various industries. Professionals in this field use mathematical modeling, data analysis, and algorithm development to optimize processes, improve efficiency, and provide data-driven recommendations. They often collaborate with data scientists, engineers, and business stakeholders to implement scalable solutions that leverage both machine learning techniques and quantitative analysis. These roles are commonly found in sectors like logistics, finance, supply chain management, and manufacturing.

How does a Machine Learning Operations Research professional typically collaborate with cross-functional teams during a project lifecycle?

Machine Learning Operations Research professionals often work closely with data scientists, software engineers, and business stakeholders throughout a project's lifecycle. They are responsible for translating business objectives into quantitative models, integrating those models into production systems, and ensuring that solutions are scalable and reliable. Regular collaboration includes discussing problem formulations with stakeholders, sharing progress with technical teams, and refining models based on feedback and operational constraints. This cross-functional teamwork helps ensure that analytical solutions are both technically robust and aligned with business goals.
Infographic showing various Machine Learning Operations Research job openings in the United States as of May 2026, with employment types broken down into 88% Full Time, and 12% Part Time. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $102,462 per year, or $49.3 per hour.
Machine Learning Engineer II, Logistics AI

Machine Learning Engineer II, Logistics AI

Instacart

San Marcos, TX

Full-time

Posted 14 days ago


Instacart rating

6.7

Company rating: 6.7 out of 10

Based on 29 frontline employees who took The Breakroom Quiz


Job description

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.

About the Role:

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart's marketplace systems. You will use machine learning to devise and refine solutions in crucial areas such as routing optimization, pricing, dispatch, and mapping. You will actively contribute to initiatives, assisting in all stages from the initial concept, through prototyping and experimentation, to final implementation.

About the Team:

The Logistics AI group is responsible for the intelligence and execution behind Instacart’s fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high quality, shoppers get efficient and fulfilling work, and retailers and consumer brands get reasonable business. The team tackles hard problems in a variety of spaces, such as matching, pricing, and geospatial, as well as foundational problems executing on a high throughput system with dynamic data.

About the Job:

  • Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace.
  • Collaborate closely with product managers, data scientists, and backend engineers to deeply understand business needs and create impactful ML/AI applications.
  • Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals.
  • Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.

About You:

Minimum Qualifications:

  • Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience 
  • Have strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and Machine Learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
  • Have strong analytical skills and problem-solving ability
  • Are a strong communicator who can collaborate with diverse stakeholders across all levels

Preferred Qualifications:

  • Have 1-2 years of industry experience using machine learning to solve real-world problems with large datasets
  • Knowledge of deep learning frameworks and methodologies
  • Experience in applying machine learning and optimization techniques to solve marketplace problems

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.


What Instacart employees say

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Hours and flexibility

Workplace

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Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012