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Volunteer Junior Machine Learning Engineer Jobs in Texas

Machine Learning Engineer

Austin, TX · On-site

$170K - $250K/yr

Your Job The ML Engineer will build physics-informed surrogate models on Azure Machine Learning that predict engineering simulation outcomes directly from design parameters. They will be pre ...

New

R249230Lead Machine Learning Engineer**Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

New

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

New

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

We are seeking an experienced Staff Machine Learning Engineer with a strong background in Large ... Mentor junior engineers and contribute to the team's knowledge sharing and best practices.

Lead Machine Learning Engineer

Plano, TX

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

We are hiring Senior Machine Learning Engineers We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and ...

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Showing results 41-60

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 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:

Machine Learning Engineer

Koch Industries

Austin, TX • On-site

$170K - $250K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Koch Industries rating

8.0

Company rating: 8.0 out of 10

Based on 53 frontline employees who took The Breakroom Quiz

138th of 543 rated manufacturers


Job description

Your Job
The ML Engineer will build physics-informed surrogate models on Azure Machine Learning that predict engineering simulation outcomes directly from design parameters. They will be pre-screening candidate designs in milliseconds so only the most promising ones require full high-fidelity simulation, accelerating the design-optimization cycle.
Our Team
Established in 1938, Molex delivers comprehensive electronic solutions for various markets, including data communications, telecommunications, consumer electronics, industrial, automotive, commercial vehicle, aerospace and defense, medical, and lighting. You'll join the platform team behind our Azure AI/ML engineering tools, partnering closely with data scientists, LLM engineers, and MLOps teams to keep GPU-heavy training and simulation workloads reliable and fast.
What You Will Do
  • Design and train surrogate models (neural networks, Gaussian processes, gradient-boosted trees, GNNs/PINNs) on Azure GPU compute (ND/NC series).
  • Incorporate physics-informed constraints so predictions stay physically valid, not just statistically fit.
  • Build model-uncertainty and confidence scoring to decide which designs need full simulation validation, then retrain as new results arrive.
  • Deploy and version models via Azure ML endpoints and model registry; monitor for drift on a rolling basis.
  • Benchmark surrogate vs. full-simulation speedup to guide platform-level performance tuning.

Who You Are (Basic Qualifications)
  • Extensive hands-on experience building, training, and deploying ML models in production - not just using pretrained APIs.
  • 10+ years building ML for physical/engineering systems (surrogate modeling, physics-informed ML, or scientific ML).
  • Strong Python with PyTorch or TensorFlow.
  • Understanding of relevant engineering/physics fundamentals and simulation data formats for your domain.
  • Experience with Azure Machine Learning or a similar cloud ML platform.
  • Familiarity with uncertainty quantification (Bayesian approaches, ensembling).

What Will Put You Ahead
  • Direct experience with industry-standard EM or physics simulation tools.
  • Geometric deep learning (graph neural networks, mesh-based models) for CAD data.
  • Background in RF/high-speed electronics or interconnect design.

For this role, we anticipate paying $170,000 - $250,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.
At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy.
Hiring Philosophy
All Koch companies value diversity of thought, perspectives, aptitudes, experiences, and backgrounds. We are Military Ready and Second Chance employers. Learn more about our hiring philosophy here .
Who We Are
As a Koch company, Molex is a leading supplier of connectors and interconnect components, driving innovation in electronics and supporting industries from automotive to health care and consumer to data communications. The thousands of innovators who work for Molex have made us a global electronics leader. Our experienced people, groundbreaking products and leading-edge technologies help us deliver a wider array of solutions to more markets than ever before.
At Koch, employees are empowered to do what they do best to make life better. Learn how our business philosophy helps employees unleash their potential while creating value for themselves and the company.
Our Benefits
Our goal is for each employee, and their families, to live fulfilling and healthy lives. We provide essential resources and support to build and maintain physical, financial, and emotional strength - focusing on overall wellbeing so you can focus on what matters most. Our benefits plan includes - medical, dental, vision, flexible spending and health savings accounts, life insurance, ADD, disability, retirement, paid vacation/time off, educational assistance, and may also include infertility assistance, paid parental leave and adoption assistance. Specific eligibility criteria is set by the applicable Summary Plan Description, policy or guideline and benefits may vary by geographic region. If you have questions on what benefits apply to you, please speak to your recruiter.
Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results.
Equal Opportunities
Equal Opportunity Employer, including disability and protected veteran status. Except where prohibited by state law, some offers of employment are conditioned upon successfully passing a drug test. This employer uses E-Verify. Please click here for additional information. (For Illinois E-Verify information click here , aquí , or tu ).

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