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Staff Machine Learning Engineer Jobs in Austin, TX

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 ...

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 ...

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 ...

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 ...

Machine Learning Engineer

Austin, TX ยท 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 ...

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Showing results 1-20

Staff Machine Learning Engineer information

See Austin, TX salary details

$22.8K

$98.5K

$190.8K

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

As of Jul 19, 2026, the average yearly pay for staff machine learning engineer in Austin, TX is $98,457.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,400.00 and $123,900.00 per year, depending on experience, location, and employer.

What does a staff ML engineer do?

A staff machine learning engineer leads the design, development, and deployment of complex machine learning models and systems. They often mentor team members, collaborate with cross-functional teams, and ensure scalable, efficient solutions using tools like Python, TensorFlow, or PyTorch. This role typically requires advanced knowledge of algorithms, data structures, and production environment considerations.

What are the typical collaboration and leadership responsibilities for a Staff Machine Learning Engineer?

As a Staff Machine Learning Engineer, you often serve as a technical leader, partnering with cross-functional teams including data scientists, product managers, and software engineers to develop and deploy machine learning solutions. You will mentor junior engineers, conduct code reviews, and help establish best practices for model development and deployment. In addition to hands-on technical work, you may be responsible for evaluating new tools, contributing to the broader ML strategy, and facilitating knowledge sharing sessions. This collaborative and leadership-focused approach helps ensure consistency, quality, and innovation across machine learning projects.

What engineer makes $500,000 a year?

Senior staff machine learning engineers at large tech companies or specialized AI firms can earn $500,000 or more annually, often including bonuses and stock options. These roles typically require advanced skills in deep learning, data engineering, and experience with cloud platforms, along with a strong track record of impactful projects.

Will MLE be replaced by AI?

Staff Machine Learning Engineers design, develop, and deploy AI models, and their role involves understanding complex algorithms and data systems. While AI automation can handle certain tasks, MLEs are essential for creating, tuning, and maintaining AI systems, making complete replacement unlikely in the near term. Continuous learning and expertise in tools like Python, TensorFlow, or PyTorch are important for the role.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer or AI research director, often involving advanced skills in deep learning, data science, and software engineering. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities, with compensation reflecting the seniority and impact of the role.

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

To thrive as a Staff Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, data analysis, and typically a strong academic background in computer science or related fields. Experience with Python, TensorFlow, PyTorch, cloud platforms, and a track record of delivering production-level ML systems are crucial, as are advanced degrees or relevant certifications. Strong leadership, communication, and mentoring skills help you effectively guide teams and collaborate across departments. These competencies are essential for designing robust ML solutions, leading technical initiatives, and ensuring successful project delivery in complex organizational environments.

What is a Staff Machine Learning Engineer job?

A Staff Machine Learning Engineer is a senior-level technical role responsible for designing, deploying, and optimizing machine learning models at scale. They provide technical leadership, mentor other engineers, and drive best practices in ML system architecture. This role often involves collaborating with cross-functional teams, improving model performance, and ensuring the reliability of machine learning solutions in production. Staff ML Engineers typically have deep expertise in algorithms, data infrastructure, and engineering processes. Their work focuses on solving complex problems and influencing the broader ML strategy within an organization.

Machine Learning Engineer

Avride

Austin, TX โ€ข On-site

Full-time

Re-posted 26 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 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 this role, you will conduct experiments, manage large-scale datasets, and implement deep learning models tailored for autonomous systems.
You will utilize cloud platforms, orchestration tools, and machine learning frameworks to develop scalable and efficient solutions. Additionally, you will analyze the latest research, assess the applicability of emerging deep learning techniques, and drive innovation in autonomous vehicle technology.
What you'll do
  • Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness. This may include developing models for understanding a self-driving vehicle's surroundings or predicting the intentions of other road users.
  • Curate and Manage Large-Scale Datasets: Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation.
  • Enhance and Maintain Training Pipelines: Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring.
  • Improve Model Deployment and Efficiency: Optimize inference performance, model compression, and deployment across various hardware platforms.
  • Explore and Apply Cutting-Edge ML Techniques: Stay up to date with advancements in deep learning and experiment with novel approaches to improve model performance.
  • Collaborate with Cross-Functional Teams: Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems.
What you'll need
  • Strong understanding of fundamental machine learning algorithms and neural network techniques.
  • Expertise in at least one modern machine learning domain, such as computer vision, large language models, or generative AI.
  • At least three years of experience developing neural network-based algorithms, including data collection, training, and deployment.
  • 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 by reviewing research papers, technical reports, and documentation.
  • Strong collaboration and communication skills, with the ability to align technical work with business objectives and drive results.
Nice to 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.
  • Proven ability to set and achieve mid- and long-term goals, prioritize tasks, and meet deadlines independently.
  • Experience working in cross-functional teams within a multidisciplinary environment.
  • Publications in top-tier ML conferences or contributions to patent applications or ML-related open-source projects.

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Candidates are required to be authorized to work in the U.S. The employer is not offering relocation sponsorship, and remote work options are not available.
Avride is an equal opportunity employer and committed to providing reasonable accommodations to qualified applicants and employees with disabilities to ensure they have equal access to employment opportunities. Avride complies with the Americans with Disabilities Act (ADA), if you need a reasonable accommodation to assist with the application or hiring process, or to perform the essential functions of a job, please email jobs@avride.ai.