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Phd Machine Learning Jobs in Texas (NOW HIRING)

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

Bachelors, Masters, or PhD in Computer Science, Statistics, or a related field * 5 years of experience in applied machine learning on real use cases * Proficient coding skills and strong software ...

Preferred Qualifications PhD or Graduate degree with research/work experience using data science ... Experience building data processing pipelines and large scale machine learning systems with ...

Preferred Qualifications PhD or Graduate degree with research/work experience using data science ... Experience building data processing pipelines and large scale machine learning systems with ...

Preferred Qualifications PhD or Graduate degree with research/work experience using data science ... Experience building data processing pipelines and large scale machine learning systems with ...

In this role, you will be directly involved in our SoC design machine learning efforts ... or PhD with relevant publications preferred but not required. Minimum Qualifications Minimum of ...

In this role, you will be directly involved in our SoC design machine learning efforts ... or PhD with relevant publications preferred but not required. Minimum Qualifications Minimum of ...

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Phd Machine Learning information

See Texas salary details

$12

$21

$28

How much do phd machine learning jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for phd machine learning in Texas is $21.26, according to ZipRecruiter salary data. Most workers in this role earn between $18.37 and $23.75 per hour, depending on experience, location, and employer.

What is a PhD in Machine Learning?

A PhD in Machine Learning is an advanced doctoral degree focused on developing new algorithms, theories, and applications in the field of machine learning. Graduates typically conduct original research, contribute to academic publications, and often specialize in areas like deep learning, reinforcement learning, or probabilistic modeling. This degree prepares individuals for careers in academia, industry research labs, or leadership roles in tech companies. The program usually involves coursework, comprehensive exams, and the completion of a dissertation based on novel research.

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

To thrive as a PhD-level Machine Learning professional, you need deep expertise in mathematics, statistics, computer science, and advanced machine learning algorithms, typically supported by a doctoral degree. Proficiency with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong problem-solving skills, critical thinking, and effective communication set outstanding candidates apart by enabling them to tackle complex research challenges and collaborate across teams. These skills and qualities are crucial for driving innovation, publishing research, and developing impactful machine learning solutions.

What are some common challenges faced by PhD-level professionals in machine learning when transitioning from academia to industry roles?

PhD graduates in machine learning often encounter challenges such as adapting to faster-paced project timelines, aligning research with business objectives, and collaborating in multidisciplinary teams. Unlike academia, where projects can be exploratory and long-term, industry roles usually require actionable results within shorter deadlines. Additionally, communicating complex technical ideas to non-technical stakeholders and prioritizing practical solutions over theoretical novelty are key adjustments. However, these challenges also present opportunities for professional growth and broader impact.

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

AspectPhd Machine LearningData Scientist
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, R&D departmentsBusiness, tech companies, analytics teams
Industry UsageResearch-focused roles, advanced algorithm developmentData analysis, model building, business insights
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, a Phd Machine Learning typically focuses on research, developing new models, and theoretical work, often in academic or R&D settings. A Data Scientist applies these techniques to solve practical business problems, analyze data, and generate insights in industry environments.

What cities in Texas are hiring for Phd Machine Learning jobs? Cities in Texas with the most Phd Machine Learning job openings:
Infographic showing various Phd Machine Learning job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $44,224 per year, or $21.3 per hour.
Machine Learning Engineer II, Logistics AI

Machine Learning Engineer II, Logistics AI

Instacart

Mckinney, TX • On-site

Full-time

Re-posted 23 days ago


Instacart rating

7.1

Company rating: 7.1 out of 10

Based on 31 frontline employees who took The Breakroom Quiz

29th of 63 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. 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

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