1

Principal Machine Learning Engineer Jobs in Texas

Machine Learning Engineer We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work ...

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $130K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

Machine Learning Engineer II

Houston, TX · On-site

$93K - $127K/yr

Machine Learning Engineer II About PROS: PROS, Inc. is the leading offer management provider to the airline industry, helping airlines deliver seamless retail experiences designed to maximize revenue ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an ...

Machine Learning Engineer II

Houston, TX

$93K - $127K/yr

Machine Learning Engineer II About PROS: PROS, Inc. is the leading offer management provider to the airline industry, helping airlines deliver seamless retail experiences designed to maximize revenue ...

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

PayPal, Inc. seeks Machine Learning Engineer in Austin, TX Job Duties: Gather, analyze and implement high-impact statistical models and AI applications in various business functional areas, focusing ...

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected ...

PayPal, Inc. seeks Machine Learning Engineer in Austin, TX Job Duties: Gather, analyze and implement high-impact statistical models and AI applications in various business functional areas, focusing ...

PayPal, Inc. seeks Machine Learning Engineer in Austin, TX Job Duties: Gather, analyze and implement high-impact statistical models and AI applications in various business functional areas, focusing ...

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected to help ...

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

next page

Showing results 1-20

Principal Machine Learning Engineer information

See Texas salary details

$68.9K

$137.2K

$198K

How much do principal machine learning engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for principal machine learning engineer in Texas is $137,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,400.00 and $161,200.00 per year, depending on experience, location, and employer.

What types of projects and responsibilities can a Principal Machine Learning Engineer typically expect in this role?

Principal Machine Learning Engineers are often tasked with leading the design, development, and deployment of large-scale machine learning models and systems that address key business challenges. In this role, you will collaborate closely with data scientists, engineers, and product managers to define project requirements, architect solutions, and ensure high-quality delivery. You may also guide research initiatives, oversee code and model reviews, and mentor junior engineers, helping to shape the technical direction of the team. Typical responsibilities can range from prototyping and optimizing algorithms to ensuring models are scalable, reliable, and aligned with organizational goals.

What are the key skills and qualifications needed to thrive in the Principal Machine Learning Engineer position, and why are they important?

To thrive as a Principal Machine Learning Engineer, you need advanced expertise in machine learning algorithms, statistical analysis, software engineering, and a strong background in computer science or related fields, often supported by a master's or PhD degree. Familiarity with tools such as Python, TensorFlow, PyTorch, cloud platforms (AWS, GCP, Azure), and relevant certifications strengthens technical capability. Leadership, strategic thinking, effective communication, and mentorship are vital soft skills for guiding teams and collaborating across departments. These competencies are essential for driving innovation, ensuring technical excellence, and influencing organizational AI initiatives.

Will MLE be replaced by AI?

Principal Machine Learning Engineers design, develop, and oversee AI and machine learning systems, and their roles involve understanding complex algorithms, data management, and model deployment. While AI automates certain tasks, MLE roles focus on building and maintaining AI infrastructure, which requires human expertise, critical thinking, and ongoing innovation that AI cannot fully replace. The role is expected to evolve alongside advancements in AI technology but remains essential for guiding AI development and ensuring ethical, effective implementation.

What does a Principal Machine Learning Engineer do?

A Principal Machine Learning Engineer leads the design, development, and deployment of machine learning models and systems. They set technical strategy, mentor engineers, and collaborate with cross-functional teams to solve complex AI challenges. Their role often includes researching new algorithms, optimizing model performance, and ensuring scalability in production environments. Additionally, they work closely with data scientists, software engineers, and product managers to align ML initiatives with business objectives.

Infographic showing various Principal Machine Learning Engineer job openings in Texas as of May 2026, with employment types broken down into 1% Internship, 94% Full Time, 2% Part Time, and 3% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $137,158 per year, or $65.9 per hour.
Machine Learning Engineer - NJ

Machine Learning Engineer - NJ

Photon

Dallas, TX

Other

Posted 28 days ago


Job description

Machine Learning Engineer

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and engineering teams to solve complex business problems, identify data-driven opportunities, and create personalized experiences for customers. You will be responsible for building end-to-end machine learning solutions, implementing models in production, and working with various data frameworks and tools such as Python, Spark, and Databricks.

Key Responsibilities
  • Analyze use cases and design appropriate analytics models using statistical and machine learning algorithms tailored to specific business requirements.
  • Develop machine learning algorithms to drive personalized customer experiences and provide actionable business insights.
  • Apply expertise in data mining and machine learning techniques, including forecasting, prediction, segmentation, recommendation, and fraud detection.
Data Engineering and Preparation
  • Extend and augment company data with third-party data to enrich analytics capabilities.
  • Enhance data collection procedures to include necessary information for building analytics systems.
  • Prepare raw data for analysis, including cleaning, imputing missing values, and standardizing data formats using Python data frameworks (e.g., Pandas, NumPy).
Machine Learning Model Implementation
  • Implement machine learning models, considering both performance and scalability using tools like PySpark in Databricks.
  • Design and build infrastructure to facilitate large-scale data analytics and experimentation.
  • Work with tools like Jupyter Notebooks for data exploration and model development.
What We're Looking For
  • Educational Background: Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A PhD is preferred but not necessary.
  • Experience:
    • At least 5 years of experience in data analytics, with a strong understanding of core statistical algorithms such as classification and regression analysis.
    • High-level knowledge of analytics use cases such as language analysis, assortment optimization, promotional planning, dynamic pricing, markdown optimization, labor scheduling, and optimization.
  • Technical Skills:
    • Strong experience with Python-based machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
    • Proficiency in using analytics platforms like Databricks for large-scale data processing.
    • At least 4 years of continuous experience with Spark, particularly PySpark implementation.
    • Hands-on experience with data processing and analysis tools such as Pandas, NumPy, and Jupyter Notebooks.