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3D Machine Learning Jobs in Austin, TX (NOW HIRING)

... machine learning compiler infrastructure like MLIR/IREE or TVM • experience in polyhedral compilation techniques Company : SEMRON develops a 3D-scaled AI inference chip, based on a new proven ...

Required : • PhD or equivalent research experience in machine learning, applied mathematics, or a ... SEMRON develops a 3D-scaled AI inference chip, based on a new proven semiconductor device. Founded ...

Experience with machine learning models and API programming is a plus. • R&D mindset with the ... Our proven technology, industrial 3D printing, has been extending the boundaries of manufacturing ...

Experience with machine learning models and API programming is a plus. R&D mindset with the will to ... Our proven technology, industrial 3D printing, has been extending the boundaries of manufacturing ...

Experience with 3D-IC, chiplet integration, or advanced packaging physical design considerations * Experience with physical implementation of machine learning accelerators, network-on-chip ...

... learning and constant innovation. Job Summary We are looking for a Staff Digital Twin Engineer to ... digital twin, machine behavior modeling and interactive 3D experiences. This role combines ...

... learning and constant innovation. Job Summary We are looking for a Staff Digital Twin Engineer to ... digital twin, machine behavior modeling and interactive 3D experiences. This role combines ...

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3D Machine Learning information

See Austin, TX salary details

$25.3K

$42.2K

$87.2K

How much do 3d machine learning jobs pay per year?

As of Jul 26, 2026, the average yearly pay for 3d machine learning in Austin, TX is $42,209.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in 3D machine learning, and how can they be addressed?

Professionals in 3D machine learning often encounter challenges such as handling large and complex datasets, managing high computational requirements, and ensuring model robustness across diverse 3D data types (e.g., point clouds, meshes, voxel grids). Addressing these challenges typically involves using efficient data preprocessing pipelines, leveraging cloud computing or advanced GPU resources, and staying updated with the latest research on 3D data augmentation and model architectures. Collaboration with multidisciplinary teams—including data engineers, computer vision experts, and domain specialists—is also crucial for overcoming technical obstacles and producing practical, scalable solutions.

What is 3D machine learning?

3D machine learning is a field of artificial intelligence focused on developing algorithms and models that can process and understand three-dimensional data. This includes tasks such as object recognition, scene reconstruction, segmentation, and analysis using 3D data formats like point clouds, meshes, or volumetric grids. Applications of 3D machine learning are found in areas like autonomous driving, robotics, medical imaging, and augmented reality. The field combines techniques from computer vision, deep learning, and geometry processing to interpret complex spatial information.

What are the key skills and qualifications needed to thrive as a 3D Machine Learning Engineer, and why are they important?

To thrive as a 3D Machine Learning Engineer, you need a solid background in computer science, mathematics, and experience with 3D data processing and machine learning algorithms, typically supported by a relevant degree. Expertise in tools and frameworks like Python, PyTorch or TensorFlow, and libraries such as Open3D or PCL is commonly required, along with familiarity with 3D data formats. Strong problem-solving skills, creativity, and effective communication set top performers apart in this role. These skills enable the development of innovative solutions for complex 3D data challenges, which are crucial for advancements in fields like robotics, computer vision, and AR/VR.

What is the difference between 3D Machine Learning vs 3D Computer Vision?

Aspect3D Machine Learning3D Computer Vision
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegree in Computer Vision, Computer Science, or related fields; experience with image processing
Work EnvironmentResearch labs, AI development teams, tech companiesImaging labs, robotics, autonomous vehicles, tech firms
Industry UsageDeveloping models for 3D data analysis, sensor data integrationProcessing 3D images, object detection, scene reconstruction

While 3D Machine Learning focuses on creating algorithms that learn from 3D data, 3D Computer Vision emphasizes interpreting and analyzing 3D visual information. Both fields often overlap but serve different primary objectives within AI and imaging applications.

What are popular job titles related to 3D Machine Learning jobs in Austin, TX? For 3D Machine Learning jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching 3D Machine Learning jobs in Austin, TX look for? The top searched job categories for 3D Machine Learning jobs in Austin, TX are:
What cities near Austin, TX are hiring for 3D Machine Learning jobs? Cities near Austin, TX with the most 3D Machine Learning job openings:
Infographic showing various 3D Machine Learning job openings in Austin, TX as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $42,209 per year, or $20.3 per hour.

Senior Perception & Tracking Engineer

Allen Control Systems

Austin, TX • On-site

$103K - $142K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 11 days ago


Job description

Company Overview

Allen Control Systems (ACS) is a cutting-edge defense startup founded by two former Navy electrical engineers with a proven track record in robotics and software. We are developing an autonomous gun turret using advanced computer vision and control systems to precisely detect, track, and neutralize enemy drones.

With an engineering-first culture, ACS values technical excellence and innovation. Backed by our founders’ successful exits from two previous ventures acquired for a combined $180M in 2022, we are committed to ensuring that the groundbreaking technologies we develop have a real-world impact.

Position Overview

We are seeking a Senior/Staff Perception and Tracking Engineer to join our team. This person will specialize in deep algorithmic understanding and production-grade software development for real-time multi-target inertial tracking for robotics and autonomous systems. In this role, you will design and implement both classical and modern deep learning algorithms for real-time perception algorithms that enable robots and autonomous systems to detect, track, and understand objects in dynamic environments. You will work closely with robotics, software, and platform engineers to develop high-performance computer vision and tracking systems that operate reliably in real-world conditions and on resource-constrained hardware. This role is ideal for engineers who enjoy solving challenging perception problems, building real-time systems, and working at the intersection of machine learning, robotics, and computer vision.

We’re hiring across multiple experience levels, including:

  • Associate Perception & Tracking Engineer

  • Perception & Tracking Engineer

  • Senior Perception & Tracking Engineer

    Your title and level will be determined based on your experience, skills, and the scope of responsibility appropriate for the role.

What You'll Do:

  • Design, implement, test, debug, and maintain core 3D Computer Vision based multi-object tracking algorithms and infrastructure, including measurement conditioning, data association, track correlation, propagation, track initialization/maintenance/deletion, and handling of track uncertainty.

  • Develop and optimize computer vision algorithms for real-time detection and tracking of small objects in robotic and autonomous systems.

  • Implement and improve object detection and multi-object tracking pipelines using modern deep learning techniques. Analyze and resolve complex tracking issues such as track fragmentation, ID switches, poor association in clutter, sensitivity to measurement quality/latency, and coordinate system challenges.

  • Train, evaluate, and deploy machine learning models for perception tasks in dynamic environments.

  • Design image preprocessing and feature extraction pipelines to improve model robustness and performance.

  • Optimize tracking pipelines for low-latency, real-time performance on embedded hardware and/or GPUs. Profile bottlenecks and apply algorithmic or implementation improvements.

  • Collaborate with robotics and software teams to integrate perception systems into autonomous platforms and real-world deployments.

  • Participate in the full software development lifecycle: requirements, design, implementation, unit/integration/system testing, deployment, and maintenance. Follow strong software engineering practices and support automated testing and evaluation frameworks.

  • Define tracking-specific metrics, evaluation harnesses, and test scenarios. Quantify and improve accuracy, robustness, stability, and computational efficiency.

Required Technical Skills:

  • 2-3 years of experience working with perception algorithms, robotics, or machine learning and comfortable in a role that specializes in 3D Computer Vision based tracking

  • Bachelor's or Master's degree in Computer Science, Aerospace Engineering, Applied Math or related field

  • Strong experience developing vision-based tracking algorithms for real-time applications

  • Experience implementing object detection (YOLO, SSD, R-CNN, or similar) and classic or deep learning-based tracking algorithms (Kalman and particle filters, ByteTrack, or similar)

  • Solid applied math foundation in linear algebra, probability, statistics, and optimal estimation (Kalman filtering and variants)

  • Experience with image preprocessing, feature extraction, and other classical computer vision pipelines

  • Strong programming skills in Python and C++

Preferred Technical Skills:

  • Production experience integrating real-time tracking algorithms into robotic perception systems on edge or embedded hardware.

  • Experience with multi-sensor fusion and integrating heterogeneous sensor data (cameras + LiDAR, RADAR, or other modalities) into tracking pipelines.

  • Ability to go beyond library usage (e.g., ByteTrack, DeepSORT) and implement or significantly customize core tracking logic.

  • Familiarity with practical tracking challenges and mitigations: measurement latency, varying update rates, coordinate transformations/registration, track-to-track fusion concepts, IMM-style maneuver modeling, and handling of redundant or conflicting measurements.

  • Experience working on robotics systems or embedded vision platforms

  • Experience optimizing vision workloads using CUDA or GPU acceleration

What We Offer

  • Competitive salary

  • Health, Dental, Vision Insurance

  • Paid Time Off

Allen Control Systems is an Equal Opportunity Employer, providing equal employment opportunities to all employees and applicants for employment. Allen Control Systems prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.