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Machine Learning Assistant Jobs in Texas (NOW HIRING)

Toyota

Sr. Machine Learning Engineer

Plano, TX · On-site

$117K - $154K/yr

You should not apply for this role if you will require Toyota to assist with immigration support or ... Toyota's Data Science department is looking for a passionate and highly motivated Machine Learning ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX

$103K - $142K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX

$103K - $142K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

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Machine Learning Assistant information

What are some common challenges a Machine Learning Assistant may face when supporting data preparation and model training?

Machine Learning Assistants often encounter challenges such as cleaning large, unstructured datasets, identifying and handling missing or inconsistent data, and ensuring data privacy compliance. They also need to communicate effectively with data scientists and engineers to understand project requirements and adapt to evolving priorities. Staying organized and managing multiple tasks simultaneously—such as data preprocessing, feature engineering, and running model experiments—is crucial for success in this role.

Is ML a high paying job?

Machine Learning Assistant roles are generally well-paying compared to many entry-level positions, with salaries often reflecting the specialized skills in programming, data analysis, and familiarity with tools like Python and TensorFlow. Compensation varies based on experience, location, and industry, but the field is known for competitive salaries and growth opportunities.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as AI executives, senior machine learning engineers, or research directors, often requiring advanced skills, extensive experience, and sometimes equity or bonuses. These positions are usually found in large tech companies or specialized AI firms and may involve leadership, strategic planning, and cutting-edge research.

Which 3 jobs will survive AI?

For a Machine Learning Assistant, roles that require complex problem-solving, creativity, and human interaction are likely to persist, such as data scientists, AI ethics specialists, and domain-specific consultants. These jobs involve nuanced judgment, ethical considerations, and contextual understanding that AI tools currently cannot fully replicate.

What is a Machine Learning Assistant?

A Machine Learning Assistant is a professional who supports the development, implementation, and maintenance of machine learning models and systems. They assist data scientists and engineers by preparing datasets, conducting preliminary data analysis, running experiments, and helping to optimize algorithms. This role often involves coding, testing models, and ensuring the quality and reliability of machine learning solutions. Machine Learning Assistants play a key role in streamlining workflows and enabling faster progress in AI projects.

What jobs pay $2000 a day?

High-paying jobs that can reach $2000 a day often include specialized roles such as senior software engineers, data scientists, or freelance consultants with in-demand skills. These positions typically require extensive experience, advanced certifications, or freelance work with high hourly rates, and may involve project-based or contract work in industries like technology, finance, or consulting.

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

To thrive as a Machine Learning Assistant, a solid background in mathematics, statistics, programming (often Python), and foundational knowledge of machine learning algorithms is essential, typically supported by a relevant degree or coursework. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems such as Git is commonly required. Strong problem-solving abilities, attention to detail, and the capability to communicate findings effectively are standout soft skills in this role. These skills ensure accurate data analysis, effective model building, and successful collaboration within multidisciplinary teams.
What are the most commonly searched types of Machine Learning jobs in Texas? The most popular types of Machine Learning jobs in Texas are:
What are popular job titles related to Machine Learning Assistant jobs in Texas? For Machine Learning Assistant jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Machine Learning Assistant jobs in Texas look for? The top searched job categories for Machine Learning Assistant jobs in Texas are:
What cities in Texas are hiring for Machine Learning Assistant jobs? Cities in Texas with the most Machine Learning Assistant job openings:
Machine Learning Assistant jobs near you
Infographic showing various Machine Learning Assistant job openings in Texas as of June 2026, with employment types broken down into 76% Full Time, 20% Part Time, 1% Contract, and 3% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior / Staff Machine Learning Infrastructure Engineer

Waabi

Dallas, TX • On-site, Remote

$157K - $234K/yr

Full-time

Posted 16 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will..
- Design, develop, and implement the machine learning platform for the continuous deployment and integration of machine learning models.
- Collaborate with data scientists and engineers to understand model requirements and optimize pipeline processes.
- Automate the training, testing and deployment processes for machine learning models.
- Continuously monitor and maintain model pipelines, ensuring optimal performance, accuracy and reliability.
- Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.
- Ensure compliance with security and data privacy standards in all MLOps activities.
 
Qualifications:
- 3-5 years of experience supporting machine learning training platforms.
- Bachelor’s degree in Computer Science, Data Science or a related field.
- Strong understanding of machine learning principles and model lifecycle management.
- Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow or PyTorch.
- Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services.
- Experience managing technology such as JupyterHub and Kubeflow.
- Familiarity with containerization and orchestration tools such as Kubernetes and Docker.
- Strong problem-solving skills and ability to troubleshoot complex issues.
- Experience with monitoring tools and practices for model performance in production.
- Ability to work collaboratively in cross-functional teams.
 
Bonus/nice to have: 
- Experience with infrastructure-as-code (IaC) tools such as Terraform or Crossplane.
- Knowledge of big data technologies like Apache Spark or Hadoop.
- Familiarity with data engineering practices and tools.
- Experience with A/B testing and model validation in production environments.
- Relevant MLOps certifications (e.g., AWS Certified Machine Learning – Specialty, DataRobot MLOps Certification) are a plus.
The US yearly salary range for this role is: $157,000 - $234,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations.  Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve! 

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.