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

CAD

Houston, TX · On-site

$25.75 - $35.50/hr

If you have a solid grasp of drafting fundamentals and a passion for learning how massive, real ... Responsibilities: * Uses 2D/3D AutoCad to develop lift plans, machinery installations and ...

CAD

Houston, TX · On-site

$25.75 - $35.50/hr

If you have a solid grasp of drafting fundamentals and a passion for learning how massive, real ... Responsibilities: * Uses 2D/3D AutoCad to develop lift plans, machinery installations and ...

CAD

Houston, TX · On-site

$25.75 - $35.50/hr

If you have a solid grasp of drafting fundamentals and a passion for learning how massive, real ... Responsibilities: * Uses 2D/3D AutoCad to develop lift plans, machinery installations and ...

Mechanical Design Engineer

Houston, TX · On-site

$72K - $98K/yr

... learning, and technical excellence. KEY RESPONSIBILITIES * Develop detailed mechanical designs using SOLIDWORKS * Design components for 3D printing, CNC machining, and injection molding * Create ...

Mechanical Design Engineer

Houston, TX · On-site

$72K - $98K/yr

... learning, and technical excellence. KEY RESPONSIBILITIES * Develop detailed mechanical designs using SOLIDWORKS * Design components for 3D printing, CNC machining, and injection molding * Create ...

Mechanical Design Engineer

Houston, TX

$72K - $98K/yr

... learning, and technical excellence. KEY RESPONSIBILITIES * Develop detailed mechanical designs using SOLIDWORKS * Design components for 3D printing, CNC machining, and injection molding * Create ...

Maker Space Technician (Part-time) Staff Pool

Houston, TX · On-site

$15.75 - $20.50/hr

... learning opportunities. The Team Play a central role at HCC as you keep our everyday operations ... machines including laser cutting systems, 3D printers, CNC routers, plasma cutters, vinyl cutters ...

Assembly Technician

Sugar Land, TX · On-site

$22 - $28/hr

... 3D computer aided design (CAD) software, and on-site manual and CNC machines, make us a one-stop ... You are committed to learning our extensive product line, from what these products do to ...

Showing results 21-40

3D Machine Learning information

See Spring, TX salary details

$22.7K

$37.9K

$78.3K

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

As of Aug 11, 2026, the average yearly pay for 3d machine learning in Spring, TX is $37,895.00, according to ZipRecruiter salary data. Most workers in this role earn between $28,900.00 and $40,900.00 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 job categories do people searching 3D Machine Learning jobs in Spring, TX look for? The top searched job categories for 3D Machine Learning jobs in Spring, TX are:
What cities near Spring, TX are hiring for 3D Machine Learning jobs? Cities near Spring, TX with the most 3D Machine Learning job openings:
Infographic showing various 3D Machine Learning job openings in Spring, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $37,895 per year, or $18.2 per hour.

Postdoctoral Fellow - Bioinformatics & Computational Biology

MD Anderson Cancer Center

Houston, TX • On-site

$64K - $76K/yr

Full-time

Medical, Dental, Retirement, PTO

Re-posted 20 days ago


MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 170 frontline employees who took The Breakroom Quiz

23rd of 887 rated healthcare providers


Job description

A full-time postdoctoral fellow position is available in Dr. Ye Zheng's lab at the Department of Bioinformatics and Computational Biology, the University of Texas MD Anderson Cancer Center. We are seeking a highly motivated and dedicated postdoctoral researcher to join our dynamic, hybrid, and highly collaborative lab. This computational postdoctoral fellow candidate is expected to leverage single-cell/bulk-cell multi-omics, spatial omics, and pathological imaging data to reveal the cancer-specific mechanisms underlying the differential efficacies and toxicities of treatments across patients. This position offers an exciting opportunity to contribute to pioneering biological, clinically important and methodologically challenging problems by innovating cutting-edge statistical models, computational methods and AI agent skills. This position provides extensive training in grant writing, with a focus on prestigious early career development grants such as the K99 and Damon Runyon awards.
Dr. Zheng's lab works on problems at the interface of statistical, computational and biomedical sciences. The lab has developed methods to decipher gene cis-regulatory mechanisms from transcriptomics, epigenomics, proteomics and three-dimensional (3D) chromatin interaction perspectives.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
The postdoctoral fellow will achieve the following learning goals: (1) develop rigorous and reproducible statistical and machine learning methods for integrating multi-modality cancer datasets, with strong benchmarking and uncertainty awareness, and deliver these methods as well documented computational tools; (2) build AI pathology models that convert tissue morphology into quantitative features to support downstream molecular interpretation, including deconvolution and harmonization approaches for robust comparison across patients, cohorts, and tissue types; (3) create agentic AI workflows that automate analysis from data ingestion and quality control to interpretation and report generation, with emphasis on transparency, auditability, and scalability on high performance computing systems; (4) conduct integrative modeling of 3D genome organization and cross platform cell surface protein measurements to improve gene regulation insight and cell type and state characterization; (5) develop professional skills through structured mentorship in manuscript writing, scientific communication, and career development applications, including K99 R00 and Damon Runyon.
ELIGIBILITY REQUIREMENTS
Candidates with a Ph.D. in Computer Science, Statistics, Biostatistics, Bioinformatics, Computational Biology, Engineering, Data Science, or a related field are encouraged to apply.
1. Solid training in statistics and mathematics:
Past course or research training in statistics, including but not limited to mathematical statistics, statistical inference, and linear regression.
2. Strong computational skills:
• Proficient in developing computational tools and modern AI agent-related workflows.
• Proficient in programming languages R, Python, and Shell, has extensive experience in using high-performance computing environments on Linux servers, and knows how to submit batch-run jobs.
• Experienced in processing and analyzing bulk/single-cell genomic data, spatial omics data, or image data.
• Ability to conduct highly organized and reproducible research.
3. Genomics knowledge:
Have experience working on genetic or genomic data. Can interpret the biological findings.
4. Strong communication, writing, and collaboration ability.
5. First, co-first, corresponding, or co-corresponding publications and reprints under review on computational and/or statistical methodology development are required to demonstrate academic writing ability.
ADDITIONAL APPLICATION INFORMATION
Lab website and potential research project descriptions: https://compbiowizard.github.io./
To apply, please email the following to Dr. Ye Zheng at yzheng8@mdanderson.org.
(1) a cover letter describing past contributions to the field, future research plan, career development plan, scientific motivation and interests that align with Dr. Zheng's lab,
(2) a curriculum vitae that includes publications and GitHub links to past project codes or developed software
(3) emails and phone numbers of a list of three references
POSITION INFORMATION
MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000 . depending on the number of years of postgraduate experience. The University of Texas MD Anderson Cancer Center offers excellent benefits , including medical, dental, paid time off , retirement , tuition benefits, educational opportunities, and individual and team recognition
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

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