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Slam Engineer Jobs in Texas (NOW HIRING)

Skyways

Senior Computer Vision Engineer

Austin, TX

$103K - $142K/yr

Mentor junior perception engineers and raise the quality bar for how perception systems are ... Background in SLAM, visual odometry, or GPS-denied navigation * Experience with embedded or real ...

Skyways

Senior Computer Vision

Austin, TX · On-site

... engineering environments • Strong communication and collaboration skills Preferred : • ... in SLAM, visual odometry, or GPS-denied navigation • Experience with embedded or real-time ...

Caterpillar

Senior Manager Robotics Engineering

Irving, TX · On-site

$172K - $258K/yr

Engineering Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're ... SLAM, AI); you don't need to be the deepest in every area, but you must earn the team's technical ...

U.S. Silica Company

Electrical Technician

Midland, TX · On-site

... programmable logic controllers (PLCs), sensors, vision inspection systems, and high-voltage ... Follows all safety requirements including but not limited to LOTO, Confined Space, SLAM, DBS ...

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See Texas salary details

$27K

$98.4K

$157.4K

How much do slam engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for slam engineer in Texas is $98,387.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,800.00 and $118,300.00 per year, depending on experience, location, and employer.

What is a slam engineer?

A SLAM (Simultaneous Localization and Mapping) Engineer develops algorithms and systems that enable machines, like robots or AR/VR devices, to map their environment while tracking their own position. They work with sensor fusion, computer vision, and machine learning to enhance real-time navigation and spatial awareness. This role is crucial in robotics, autonomous vehicles, and augmented reality applications. A SLAM Engineer typically has expertise in C++, Python, ROS, and technologies like LiDAR and visual odometry.

What are the main projects and responsibilities I can expect as a slam engineer?

As a SLAM Engineer, you'll typically be responsible for developing, optimizing, and integrating algorithms that enable robots or autonomous devices to navigate and map their environments. This may involve working with sensor data from LiDAR, cameras, or IMUs, implementing real-time data processing pipelines, and testing your solutions in both simulated and real-world scenarios. You’ll often collaborate closely with robotics hardware engineers, software developers, and research scientists to ensure reliable system performance. Additionally, you may participate in field deployments, debugging sessions, and ongoing enhancements to keep up with the latest research and industry trends.

What are the key skills and qualifications needed to thrive in the slam engineer position, and why are they important?

To thrive as a SLAM Engineer, you need expertise in robotics, computer vision, and probabilistic state estimation, usually supported by a degree in computer science, robotics, or electrical engineering. Familiarity with tools like ROS (Robot Operating System), C++/Python programming, and experience with libraries such as OpenCV, PCL, or GTSAM are typically required. Strong problem-solving ability, attention to detail, and effective teamwork are crucial soft skills in this position. These capabilities are vital for developing and maintaining robust simultaneous localization and mapping solutions, ultimately ensuring high-performance autonomous systems.

How much do slam engineers make?

Slam engineers typically earn a median annual salary ranging from $70,000 to $120,000, depending on experience, location, and industry. They often require knowledge of robotics, automation, and control systems, and may work in manufacturing, logistics, or research environments.

What are the most commonly searched types of Slam Engineer jobs in Texas?

The most popular types of Slam Engineer jobs in Texas are:

What are popular job titles related to Slam Engineer jobs in Texas?

For Slam Engineer jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Slam Engineer jobs in Texas look for?

The top searched job categories for Slam Engineer jobs in Texas are:

What cities in Texas are hiring for Slam Engineer jobs?

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Slam Engineer jobs near you
Infographic showing various Slam Engineer job openings in Texas as of August 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $98,387 per year, or $47.3 per hour.

Machine Learning Engineer - Motion Planning & Prediction

Avride

Austin, TX • On-site

$138K/yr

Full-time

Re-posted 26 days ago

Job description

About the team
Our team develops the core software and data processing systems that power motion planning and decision-making in autonomous vehicles. We work at the intersection of machine learning, large-scale data infrastructure, and real-time vehicle control, collaborating across engineering, analytics, and product teams to deliver safe and intelligent driving capabilities.
Before you apply: This role requires hands-on experience building systems that predict how other agents will move and deciding how a vehicle or robot should act in response - deployed on real hardware, not only in simulation or research. If your machine learning experience is primarily in NLP, recommendations, tabular data, or academic research without deployed systems, this specific role likely isn't the right fit, though we encourage you to look at our other openings
About the role
We are looking for a creative & driven Machine Learning Engineer to join our autonomous vehicle team. You will be at the center of our efforts to build intelligent systems that can understand, predict, and safely navigate a complex and dynamic world. This role involves designing and training the next generation of deep learning models that form the brain of our vehicle, learning from petabytes of real-world driving data. If you are passionate about applying cutting-edge ML to solve high-stakes robotics challenges, we want to hear from you.
About the Team
We build the software that decides how our autonomous vehicles move through the world. Our systems predict the behavior of pedestrians, cyclists, and other vehicles, then plan trajectories that are safe, comfortable, and legible to the people around them. We work at the intersection of machine learning, real-time systems, and large-scale data infrastructure - and everything we build runs on vehicles operating in real traffic.
About the Role
You will design and train the models that anticipate what other road users will do next, and turn those predictions into driving decisions. This means working with petabytes of real driving data, building evaluation frameworks that actually correlate with on-road safety, and shipping models that run under hard latency budgets on embedded hardware.
This is a production engineering role. You will spend meaningful time on failure analysis, long-tail scenarios, and the gap between offline metrics and on-road behavior.
What You'll Do
  • Design, train, and deploy models for behavioral prediction and motion planning that run on vehicles in real traffic
  • Model multi-agent interaction and temporal dynamics - how a merge, an unprotected left, or an occluded pedestrian actually unfolds
  • Own the metrics: build evaluation frameworks that correlate with real on-road safety and performance, not just offline loss
  • Diagnose long-tail failures from real driving logs and close the loop back into training data and model design
  • Optimize trained models for real-time inference under strict latency, memory, and compute constraints on embedded hardware
  • Build and maintain data pipelines that process, clean, and label large-scale vehicle sensor and simulation datasets
What You'll Need
Domain experience (required):
  • Hands-on experience with at least one of: behavioral or trajectory prediction, motion planning, decision-making under uncertainty, or closely adjacent autonomy work (navigation, SLAM, control, or perception-for-planning) for autonomous vehicles, mobile robots, drones, or comparable physical systems
  • Experience deploying machine learning to real hardware operating in the physical world, under real-time or resource constraints. Simulation-only or offline-only experience does not meet this bar.

Engineering (required):
  • Strong Python and production experience with a modern deep learning framework (PyTorch, TensorFlow, or JAX)
  • Proficiency in C++ (or Rust) for performance-critical inference and integration code
  • Demonstrated ownership of a system from prototype through deployment, including debugging it after it shipped

How we evaluate: We weight what you have actually built and shipped far more heavily than credentials. We regularly hire people without advanced degrees and without prior autonomous-vehicle experience. What we look for is specific, verifiable engineering work systems you built, constraints you worked under, and failures you diagnosed and fixed
#LI-MS1
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.

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