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Online Machine Learning Jobs in Utah (NOW HIRING)

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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 ...

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 ...

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 ...

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 ...

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 ...

Showing results 21-40

Online Machine Learning information

See Utah salary details

$23.2K

$38.8K

$80.1K

How much do online machine learning jobs pay per year?

As of Aug 7, 2026, the average yearly pay for online machine learning in Utah is $38,767.00, according to ZipRecruiter salary data. Most workers in this role earn between $29,600.00 and $41,900.00 per year, depending on experience, location, and employer.

What is online machine learning?

Online machine learning is a method where models are trained incrementally as new data becomes available, rather than being trained all at once on a fixed dataset. This approach is particularly useful in environments where data arrives continuously, such as real-time analytics, recommendation systems, and fraud detection. Online learning algorithms update their knowledge with each new data point, allowing them to adapt quickly to changes and trends. This makes them ideal for applications that require immediate responses and adaptability to evolving data streams.

What is the difference between Online Machine Learning vs Data Scientist?

AspectOnline Machine LearningData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related fields; certifications in ML or data analysisBachelor's or master's in CS, statistics, or related fields; advanced degrees often preferred
Work EnvironmentTech companies, startups, research labs; focus on real-time data processingCorporate, consulting, or research settings; focus on data analysis and modeling
Industry UsageMachine learning applications, AI development, real-time systemsData analysis, predictive modeling, business insights

Online Machine Learning specialists focus on developing algorithms that learn continuously from streaming data, often in real-time environments. Data Scientists analyze large datasets to extract insights, build models, and support decision-making. While both roles require knowledge of machine learning, Online Machine Learning emphasizes real-time data processing, whereas Data Scientists focus on data analysis and modeling for strategic insights.

How does collaboration typically work between online machine learning engineers and data scientists in a project setting?

Online machine learning engineers often work closely with data scientists to ensure that the models they develop can be effectively deployed and updated in real-time environments. While data scientists may focus on feature engineering, model selection, and initial training using historical data, online machine learning engineers are responsible for integrating these models into production systems and implementing mechanisms for continuous learning from live data streams. Regular meetings, code reviews, and shared documentation are common practices to facilitate smooth collaboration and ensure that the models remain accurate and efficient as new data arrives.

What are the key skills and qualifications needed to thrive as an online machine learning engineer?

To excel as an Online Machine Learning Engineer, you need a strong background in computer science, statistics, and machine learning algorithms, often supported by a relevant degree and experience with streaming data. Familiarity with tools such as Apache Kafka, Spark Streaming, Python, TensorFlow, and real-time data processing frameworks is critical. Problem-solving ability, adaptability, and effective communication are essential soft skills for collaborating with multidisciplinary teams and responding to rapidly changing data. These competencies are crucial for building scalable, responsive models that provide timely insights in dynamic production environments.
What are the most commonly searched types of Machine Learning jobs in Utah? The most popular types of Machine Learning jobs in Utah are:
What cities in Utah are hiring for Online Machine Learning jobs? Cities in Utah with the most Online Machine Learning job openings:
Infographic showing various Online Machine Learning job openings in Utah as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $38,767 per year, or $18.6 per hour.

Machine Learning Engineer (PhD Intern)

Instacart

West Jordan, UT

Full-time

Re-posted 17 days ago


Instacart rating

7.1

Company rating: 7.1 out of 10

Based on 31 frontline employees who took The Breakroom Quiz

27th of 64 rated delivery companies


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.

Overview

Since 2012, Instacart has been focused on making grocery delivery convenient, affordable, and accessible to everyone. We bring fresh groceries and everyday essentials to customers across the US and Canada from nearly 55,000 stores across 5,500 markets. Our mission is to create a world where everyone has access to the food they love, and to achieve that goal, we innovate in a wide range of areas including e-commerce, advertising, and fulfillment.

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we build product and knowledge graphs on top of the catalog data to support a wide range of applications including search and ads.

We are looking for talented Ph.D. students to have an internship in our fast moving team. You will have the opportunity to work on a very large scope of problems in search, ads, personalization, recommendation, fulfillment, product and knowledge graph, pricing, etc.

About the Team:

This is a general posting for multiple intern roles open across our various ML teams. You can find a blurb on each team below:

Economics Team: The Economics team at Instacart works on a range of interesting and challenging problems, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making. Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference.

Search & Discovery ML: The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search technology at Instacart. They collaborate on building models that enhance relevance of all shopping surfaces, ranking, and personalization, delivering highly relevant results to users across the Instacart ecosystem. As part of the Search and Discovery ML team, you'll work on one of the most critical aspects of the business, helping customers connect with the right products. We are passionate about solving large-scale search challenges and creating innovative solutions that elevate the customer experience. (Recent publications 1, 2, 3, 4, 5).

Content AI Team: The Content AI team at Instacart works alongside world-class engineers, data scientists, and product managers to advance generative AI, recommendations, and catalog intelligence in grocery ecommerce. We build cutting-edge AI models that power real-time recommendations, feed ranking, and automated content generation, ensuring high-quality and engaging customer experiences. Beyond recommendations, we leverage generative AI and LLMs to enhance and enrich Instacart’s catalog, driving AI-powered product understanding and content creation at scale. As part of Content AI, you'll work on high-impact AI solutions, applying LLMs, agentic systems, and computer vision to tackle complex challenges. We are passionate about pushing the boundaries of generative AI to shape the future of ecommerce. If you're excited about building state-of-the-art AI systems, we’d love to have you on board!

Past internship contributions include:

Tensor-based complementary recommendations, published at IEEE Big Data 2021 (Paper) Enhancing sequence-based recommendations for long-tail products (Blog)

About the Job

Based on your passion and background, you may choose to work in a few different areas:

  • Query understanding - Using cutting-edge NLP technologies to understand the intent of user queries.
  • Search relevance and ranking - Improving search relevance by incorporating signals from various sources.
  • Ads quality, pCTR, etc. - Improving ads revenue and ROAS.
  • Knowledge graphs - Working on graph data management and knowledge discovery, and creating a natural language interface for data access.
  • Fraud detection and prevention - Using cost sensitive learning to reduce loss.
  • Pricing - Estimating willingness-to-pay, and optimizing revenue and user experience.
  • Logistics - Optimization in a variety of situations, including supply/demand prediction, last mile delivery, in-store optimization, etc.

About You

Minimum Qualifications:

  • Ph.D. student in computer science, mathematics, statistics, economics, or related areas.
  • Strong programming (Python, C++) and algorithmic skills.
  • Good communication skills. Curious, willing to learn, self-motivated, hands-on.

Preferred Qualifications:

  • Ph.D. student at a top tier university in the United States
  • Prior internship/work experience in the machine learning space

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.


What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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