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Research Assistant Machine Learning Jobs in Austin, TX

Avride

Machine Learning Engineer

Austin, TX · On-site

Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems. Qualifications : Required : • Strong ...

Q2

Machine Learning Engineer

Austin, TX

  • Medical

... research and experimentation to advance machine learning capabilities Collaborate with cross-functional teams to integrate AI solutions into production environments Analyze large datasets to extract ...

Q2 India

Machine Learning Engineer

Austin, TX · On-site

$100 - $130/hr

  • Medical

RESPONSIBILITIES** • Design and implement machine learning algorithms and models for various business applications • Conduct research and experimentation to advance machine learning capabilities ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

  • Medical

... research and experimentation to advance machine learning capabilities • Collaborate with cross-functional teams to integrate AI solutions into production environments • Analyze large datasets to ...

Neuralink

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Formulate research questions to guide the development of neural networks and signal processing ... for machine learning applications for BCI. * Lead the team by performing at a high standard ...

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

Research and implement ML algorithms for a variety of business problems * Automate processes for ... Machine learning (ML) algorithms * Predictive modeling and analysis * Data visualization software ...

Neuralink

Machine Learning Engineer

Austin, TX

Formulate research questions to guide the development of neural networks and signal processing ... for machine learning applications for BCI. * Lead the team by performing at a high standard ...

News Corporation

Senior Manager, Machine Learning

Austin, TX · On-site

$120 - $160/hr

  • Medical

  • Dental

  • Vision

  • Retirement

... concepts, research, predictive modeling, and machine learning algorithms. You will serve as a ... You will be expected to utilize AI coding assistants and LLMs proficiently to accelerate ...

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How much do research assistant machine learning jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for research assistant machine learning in Austin, TX is $21.72, according to ZipRecruiter salary data. Most workers in this role earn between $18.37 and $25.24 per hour, depending on experience, location, and employer.

What is a research assistant machine learning?

A Research Assistant in Machine Learning supports research projects by implementing algorithms, analyzing data, and conducting experiments to advance AI models. They assist senior researchers by preprocessing datasets, developing machine learning models, and evaluating their performance. Responsibilities may also include coding, literature reviews, and writing research papers. This role is typically found in academia, research labs, or industry R&D teams. Strong programming skills, statistical knowledge, and familiarity with ML frameworks like TensorFlow or PyTorch are essential.

What types of projects might a research assistant machine learning typically work on?

As a Research Assistant in Machine Learning, you may be involved in projects such as developing and evaluating predictive models, processing and analyzing large datasets, and assisting in the publication of research findings. Your work could contribute to applications like natural language processing, computer vision, or recommendation systems, depending on the focus of the research group. You’ll often collaborate closely with senior researchers, data scientists, or PhD students, allowing you to participate in brainstorming sessions, code development, and experimental design. This experience provides valuable exposure to cutting-edge technology and can serve as a strong foundation for a research or industry career in machine learning.

What are the key skills and qualifications needed to thrive as a research assistant machine learning?

To thrive as a Research Assistant Machine Learning, you need a solid understanding of machine learning algorithms, programming skills (especially in Python or R), and a background in statistics or computer science, often supported by a bachelor’s or master’s degree. Experience with frameworks such as TensorFlow, PyTorch, and data analysis tools, as well as familiarity with version control systems like Git, is highly beneficial. Strong problem-solving abilities, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills ensure you can contribute meaningfully to research projects, analyze complex datasets, and communicate findings effectively within interdisciplinary teams.

What are popular job titles related to Research Assistant Machine Learning jobs in Austin, TX? For Research Assistant Machine Learning jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Research Assistant Machine Learning jobs in Austin, TX look for? The top searched job categories for Research Assistant Machine Learning jobs in Austin, TX are:
What cities near Austin, TX are hiring for Research Assistant Machine Learning jobs? Cities near Austin, TX with the most Research Assistant Machine Learning job openings:
Research Assistant Machine Learning jobs near you
Infographic showing various Research Assistant Machine Learning job openings in Austin, TX as of August 2026, with employment types broken down into 77% Full Time, and 23% Part Time. Highlights an 100% In-person job distribution, with an average salary of $45,171 per year, or $21.7 per hour.

Machine Learning Engineer

Avride

Austin, TX • On-site

Full-time

Re-posted 20 days ago

Job description

Job Summary:
Avride develops autonomous vehicle and delivery robot technology, and they are seeking an experienced Machine Learning Engineer to enhance their autonomous systems. The role involves developing and optimizing machine learning models, managing large-scale datasets, and collaborating with cross-functional teams to integrate solutions into real-world applications.
Responsibilities:
• Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness. This may include developing models for understanding a self-driving vehicle’s surroundings or predicting the intentions of other road users.
• Curate and Manage Large-Scale Datasets: Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation.
• Enhance and Maintain Training Pipelines: Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring.
• Improve Model Deployment and Efficiency: Optimize inference performance, model compression, and deployment across various hardware platforms.
• Explore and Apply Cutting-Edge ML Techniques: Stay up to date with advancements in deep learning and experiment with novel approaches to improve model performance.
• Collaborate with Cross-Functional Teams: Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems.
Qualifications:
Required:
• Strong understanding of fundamental machine learning algorithms and neural network techniques.
• Expertise in at least one modern machine learning domain, such as computer vision, large language models, or generative AI.
• At least three years of experience developing neural network-based algorithms, including data collection, training, and deployment.
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, along with PySpark, NumPy, and SciPy.
• Working knowledge of C++ and SQL.
• Ability to quickly absorb new concepts by reviewing research papers, technical reports, and documentation.
• Strong collaboration and communication skills, with the ability to align technical work with business objectives and drive results.
Preferred:
• Advanced degree in Computer Science, Machine Learning, Robotics, or a related field.
• Experience developing ML algorithms for autonomous vehicles or robotics applications.
• Familiarity with neural network deployment and optimization tools such as triton, TensorRT, or similar frameworks.
• Proven ability to set and achieve mid- and long-term goals, prioritize tasks, and meet deadlines independently.
• Experience working in cross-functional teams within a multidisciplinary environment.
• Publications in top-tier ML conferences or contributions to patent applications or ML-related open-source projects.
Company:
Avride is a developer and operator of autonomous vehicles and delivery robots. Founded in 2017, the company is headquartered in Austin, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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