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3D Machine Learning Jobs in Michigan (NOW HIRING)

Autodesk

Software Architect

Novi, MI · On-site +1

$143K - $256K/yr

Job Requisition ID # 26WD96433 Position Overview At Autodesk, we are pioneers in 3D design ... Working knowledge of LLMs and machine learning, with an understanding of key concepts and hands-on ...

Britten, Inc.

Machinist

Traverse City, MI · On-site

$20.25 - $27.50/hr

Responsible for machine's preventative maintenance * Being part of a team that works to drive ... Learning and adhering to safety requirements * Interest and ability to work long hours and weekend ...

Britten Inc.

Machinist

Traverse City, MI · On-site

$20.25 - $27.50/hr

Responsible for machine's preventative maintenance * Being part of a team that works to drive ... Learning and adhering to safety requirements * Interest and ability to work long hours and weekend ...

Britten, Inc.

Machinist

Traverse City, MI · On-site

$20.25 - $27.50/hr

Responsible for machine's preventative maintenance * Being part of a team that works to drive ... Learning and adhering to safety requirements * Interest and ability to work long hours and weekend ...

HARMAN International

Software Developer

Novi, MI · On-site

Research and integrate emerging technologies in WebGL, Machine Learning, and Cloud-based ... Web-Based 3D & Visualization: Experience with WebGL or browser-based 3D frameworks (e.g., Three.js ...

Adidev Technologies Inc

Civil Engineer

Detroit, MI · Hybrid

$45 - $60/hr

... and Machine Learning Engineers, and partner with municipalities, transportation authorities ... AutoCAD, Civil 3D, BIM, or similar engineering software -Understanding of codes, standards ...

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3D Machine Learning information

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 Michigan? For 3D Machine Learning jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching 3D Machine Learning jobs in Michigan look for? The top searched job categories for 3D Machine Learning jobs in Michigan are:
What cities in Michigan are hiring for 3D Machine Learning jobs? Cities in Michigan with the most 3D Machine Learning job openings:
3D Machine Learning jobs near you
Can we discuss the role of Autonomous Driving Vehicle Perception Engineer

Can we discuss the role of Autonomous Driving Vehicle Perception Engineer

INA Solution Inc

Northville, MI • On-site

Full-time

Posted 7 days ago

Be an early applicant

Job description

Job Title: Autonomous Driving Vehicle Perception Engineer

Location: Northville, MI (Onsite)

Duration: Full Time

What You will Do:

  • Design and implement advanced perception algorithms for autonomous vehicles using LiDAR, cameras, radar, and GNSS.
  • Develop and optimize sensor fusion techniques to combine data from multiple sensors, improving the accuracy and reliability of perception systems.
  • Create algorithms for object detection, tracking, semantic segmentation, and classification from 3D point clouds (LiDAR) and camera data.
  • Work on Simultaneous Localization and Mapping (SLAM) algorithms, including Graph SLAM, LIO-SAM, and visual-inertial SLAM.
  • Develop sensor calibration techniques (intrinsic and extrinsic) and coordinate transformations between sensors.
  • Participate in real-time systems design and optimization to meet the high-performance requirements of autonomous driving.
  • Work with ROS2 for integration and deployment of perception algorithms.
  • Develop, test, and deploy machine learning models for perception tasks such as object detection and segmentation.
  • Collaborate with cross-functional teams, including software engineers, data scientists, and hardware teams, to deliver end-to-end solutions.
  • Stay up-to-date with industry trends and emerging technologies to innovate and improve perception systems.

What You Will Bring:

  • Minimum 3+ years of experience in sensor calibration, multi-sensor fusion, or related domains.
  • Strong foundation in linear algebra, 3D geometry, coordinate frames, quaternions, probability, Bayesian filtering, and data association.
  • Hands-on experience with intrinsic and extrinsic calibration of LiDAR, cameras, and radar, including geometric calibration, coordinate transforms, and sensor synchronization.
  • Proven experience with perception algorithms for autonomous systems, particularly in the areas of LiDAR, camera, radar, GNSS, or other sensor modalities.
  • Deep understanding of LiDAR technology, point cloud data structures, and processing techniques; experience with PCL or Open3D.
  • Proficiency in sensor fusion for combining data from LiDAR, camera, radar, and GNSS, including handling time synchronization and motion distortion.
  • Solid background in computer vision techniques; experience with OpenCV and object detection models such as YOLO, Faster R-CNN, or SSD.
  • Experience with deep learning frameworks (TensorFlow or PyTorch) for object detection and segmentation tasks.
  • Hands-on experience with multi-object tracking algorithms such as SORT, DeepSORT, Kalman Filters, UKF, IMM, or JPDA.
  • Strong programming skills in C++ and Python; familiarity with geometric optimization libraries.
  • Familiarity with ROS2 for perception-based autonomous systems development.
  • Experience with parallel computing for real-time performance optimization (e.g., CUDA, OpenCL).