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Volunteer Junior Machine Learning Engineer Jobs in Texas

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

Neuralink

Machine Learning Engineer

Austin, TX · 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 ...

Neuralink

Machine Learning Engineer

Austin, TX · 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 ...

Neuralink

Machine Learning Engineer

Austin, TX

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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Volunteer Junior Machine Learning Engineer information

What is a volunteer junior machine learning engineer?

Volunteer Junior Machine Learning Engineers are individuals who offer their time and skills, often without pay, to assist in machine learning projects. They typically have foundational knowledge in programming, data analysis, and machine learning concepts, and they work under the guidance of experienced engineers or data scientists. Their responsibilities may include data preprocessing, building and testing models, and supporting research or development efforts. These roles provide valuable hands-on experience and are often sought after by students or career changers looking to break into the field.

What types of projects and tasks can a volunteer junior machine learning engineer expect to work on, and how do these contribute to skill development?

As a Volunteer Junior Machine Learning Engineer, you will typically assist with data preparation, exploratory data analysis, and building or improving basic machine learning models under the supervision of more experienced engineers. You may also help with tasks such as cleaning datasets, implementing algorithms, and evaluating model performance. These projects are designed to provide hands-on experience and mentorship, helping you develop technical skills while learning collaborative workflows in a team setting. This role is a great opportunity to build your portfolio, gain real-world experience, and network within the machine learning community.

What are the key skills and qualifications needed to thrive as a volunteer junior machine learning engineer, and why are they important?

To thrive as a Volunteer Junior Machine Learning Engineer, you need a foundational understanding of programming (especially Python), mathematics, and basic machine learning concepts, often supported by coursework or online certifications. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems like Git is usually expected. Curiosity, teamwork, and strong problem-solving skills help you learn quickly and contribute effectively in a collaborative environment. These skills and qualities ensure you can support real projects, continue developing your expertise, and add value even at an entry or volunteer level.

What is the difference between Volunteer Junior Machine Learning Engineer vs Volunteer Data Analyst?

AspectVolunteer Junior Machine Learning EngineerVolunteer Data Analyst
Required CredentialsBasic programming, introductory ML knowledge, possibly some courseworkData analysis skills, Excel, SQL, basic statistics
Work EnvironmentTech-focused projects, coding, model developmentData interpretation, reporting, visualization
Employer & Industry UsageTech companies, research projects, startupsNonprofits, research institutions, business analytics

The Volunteer Junior Machine Learning Engineer and Volunteer Data Analyst roles both involve working with data, but the ML engineer focuses on developing machine learning models and algorithms, requiring some programming and ML knowledge. The Data Analyst primarily interprets data through visualization and reporting, often using tools like Excel and SQL. Both roles are valuable in various industries, but the ML engineer role emphasizes technical model development, while the Data Analyst role centers on data interpretation and communication.

What are popular job titles related to Volunteer Junior Machine Learning Engineer jobs in Texas?

For Volunteer Junior Machine Learning Engineer jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Volunteer Junior Machine Learning Engineer jobs in Texas look for?

The top searched job categories for Volunteer Junior Machine Learning Engineer jobs in Texas are:

What cities in Texas are hiring for Volunteer Junior Machine Learning Engineer jobs?

Cities in Texas with the most Volunteer Junior Machine Learning Engineer job openings:

Volunteer Junior Machine Learning Engineer jobs near you

Machine Learning Engineer

Quarterhill

Frisco, TX • On-site

Full-time

Medical, Dental, Retirement, PTO

Re-posted 6 days ago

Job description

Overview
Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems. In this role, you will design, develop, and deploy state-of-the-artcomputer vision and language models that power scalable, real-world solutions. You'll work with large-scale image and video data, building and optimizing production-grade vision systems while contributing clean and modular code to shared repositories.
As part of our AI team, you'll collaborate closely with engineering teams to deliver high-impact features for our growing SaaS platform. The ideal candidate brings hands-on experience deploying computer vision and language models in production and applying MLOps best practices on cloud platforms.
Responsibilities
  • Fine-tune and deploy computer vision and deep learning models for object detection, object tracking, and OCR at scale.
  • Develop vision-language models and Mixture of Experts architectures, from experimental design through production deployment.
  • Architect Retrieval-Augmented Generation (RAG) systems, including vector store design, hybrid search strategies, chunking pipelines, and context relevance evaluation.
  • Apply MLOps best practices for training, evaluation, deployment, and monitoring of production grade computer vision models, with an emphasis on clean, modular, maintainable code.
  • Contribute to our machine learning repositories and optimize models for performance, scalability, and real-time inference across edge and cloud environments.
  • Drive performance optimization and scalability of ML systems across edge and cloud environments.
  • Collaborate with cross-functional teams to integrate computer vision solutions into end-to-end products, translating research outcomes into measurable platform impact.

This list of responsibilities might not cover everything you'll end up doing.
Qualifications
  • 5+ years of hands-on machine learning experience, with deep specialization in computer vision and a proven track record of shipping models to production.
  • Master's degree required (Ph.D. preferred) in Computer Science, Machine Learning, or a closely related field.
  • Extensive knowledge of computer vision architectures such as Vision Transformers and VLMs along with OpenCV and PIL.
  • Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes) able to own the full model lifecycle from experimentation through production monitoring.
  • Experience building and deploying LLM-based systems and Retrieval-Augmented Generation (RAG) pipelines, including vector store integration and retrieval evaluation.
  • Strong communicator who can translate complex research findings into actionable decisions for engineering and product stakeholders.

Benefits
We offer a Total Rewards plan designed with you and your family's health and wellness in mind that includes:
  • Paid days off (i.e. vacation, sick days, bereavement leave)
  • Health and Dental plans
  • Retirement plans
  • Employee and Family Assistance Program (EFAP)
  • Employee referral program

We welcome applicants from all backgrounds, regardless of race, color, religion, sex, veteran status, sexual orientation, gender identity, national origin, age, or disability or any other protected characteristics in accordance with applicable federal, state/provincial, and local laws. We're committed to creating a workplace where everyone feels valued and respected.
We appreciate all responses and will acknowledge only those being considered for an interview.
We respectfully request no calls or unsolicited resumes from Agencies.

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