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Principal Machine Learning Engineer Jobs in Texas

About the Role We are hiring experienced Machine Learning Engineers across Senior, Staff, and Principal levels. to site onsite in Austin, Texas. Whether you're a strong individual contributor ready ...

About the Role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI/ Westlake, TX/ Durham, NC/ Covington, KY/ Jersey City, NJ/ Boston, MA Candidate should be local or ...

About the Role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

About the Role As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building and scaling our AI-powered logistics solutions. You'll design, develop, and maintain the data ...

Machine Learning Engineer

Austin, TX · On-site

$132K - $244K/yr

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $129K/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 ...

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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.

Senior / Staff Machine Learning Engineer

Avride

Austin, TX

$124K - $171K/yr

Other

Posted 11 days ago


Job description

About the Team

Avride develops autonomous vehicle and delivery robot technology, leveraging deep expertise in autonomous systems. With the recent launch of our robotaxi service in Dallas, we are accelerating innovation and redefining the future of mobility. Our team builds self-driving solutions from the ground up, with machine learning at the core of our development pipeline to enable safe and intelligent navigation. We design and deploy state-of-the-art models to address key challenges in autonomous systems, utilizing advanced deep learning architectures such as Convolutional Neural Networks (CNNs), Transformers, and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard applications, ensuring robust and efficient operation. Your work will directly contribute to enhancing the performance, safety, and reliability of Avride's autonomous vehicles and delivery robots.

About the Role

We are hiring experienced Machine Learning Engineers across Senior, Staff, and Principal levels. to site onsite in Austin, Texas. Whether you're a strong individual contributor ready to take on complex technical challenges, or a seasoned technical leader looking to take on complex technical challenges we want to hear from you.
In this role, you will drive the development and deployment of machine learning solutions for some of the hardest problems in autonomy conducting experiments, managing large-scale datasets, and implementing deep learning models tailored for real-world autonomous systems. At more senior levels, you will also define technical strategy, mentor engineers, and influence how ML is practiced across the organization.

What You'll Do
  • Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness - including models for environmental perception and predicting the behavior of other road users. At Staff and Principal levels, you will set the technical vision for entire model families and drive architectural decisions across teams.
  • Curate and Manage Large-Scale Datasets: Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation. Senior+ engineers will establish standards and tooling that scale across the organization.
  • Enhance and Maintain Training Pipelines: Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring. Staff and Principal engineers will own the long-term roadmap for training infrastructure.
  • Improve Model Deployment and Efficiency: Optimize inference performance, model compression, and deployment across various hardware platforms.
  • Explore and Apply Cutting-Edge ML Techniques: Stay current with advancements in deep learning and lead the evaluation and adoption of novel approaches. Principal engineers are expected to identify opportunities before they become industry standard.
  • Collaborate and Lead Across Teams: Work closely with researchers, software engineers, and robotics experts to integrate ML into real-world autonomous systems. At Staff and Principal levels, you will drive alignment across functions, mentor junior and senior engineers, and serve as a technical authority across the org.
What You'll Need
  • Strong understanding of fundamental machine learning algorithms and neural network techniques.
  • Deep expertise in at least one modern ML domain, such as computer vision, large language models, or generative AI.
  • Senior: 4+ years of experience developing neural network-based algorithms, including data collection, training, and deployment.
  • Staff: 7+ years of experience, with a track record of leading significant technical initiatives and influencing engineering practices beyond your immediate team.
  • Principal: 10+ years of experience, with demonstrated impact at an organizational or industry level - setting multi-year technical direction and driving outcomes across multiple teams.
  • Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, along with PySpark, NumPy, and SciPy.
  • Working knowledge of C++ and SQL.
  • Ability to quickly absorb new concepts from research papers, technical reports, and documentation.
  • Strong collaboration and communication skills, with the ability to align technical work with business objectives at all levels of the organization.
What You Must Have
  • Advanced degree in Computer Science, Machine Learning, Robotics, or a related field.
  • Experience developing ML algorithms for autonomous vehicles or robotics applications.
  • Familiarity with neural network deployment and optimization tools such as Triton, TensorRT, or similar frameworks.
  • Publications in top-tier ML conferences, contributions to patent applications, or ML-related open-source projects.
  • For Staff/Principal: experience building and scaling ML teams, defining org-wide technical standards, or driving cross-company research agendas