2

Remote Machine Learning Jobs in Austin, TX (NOW HIRING)

Machine Learning Engineer Austin, TX About the Team Avride develops autonomous vehicle and delivery ... The employer is not offering relocation sponsorship, and remote work options are not available.

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

About the Role As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building and scaling our AI-powered logistics solutions. You'll design, develop, and maintain the data ...

Senior Machine Learning Engineer

Austin, TX ยท On-site +1

$121.40K - $160K/yr

Senior Machine Learning Engineer Austin, Texas or Remote Build, Deploy, and Maintain AI for an Unpredictable World Striveworks helps organizations harness the power of artificial intelligence to ...

Data Engineer (Machine Learning)

Austin, TX ยท Remote

$113.50K - $136.30K/yr

Data Engineer (Machine Learning) Location: 100% Remote Duration: Long Term Contract (2+ years) Role Overview The team builds data and machine learning services for advertiser sellers, helping them ...

Senior Machine Learning Engineer

Austin, TX ยท On-site +1

$121.40K - $160K/yr

We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems and Auction ... remote work except for employees whose roles are required to be in the office five days a week or ...

Senior Machine Learning Engineer

Austin, TX ยท On-site +1

$121.40K - $160.10K/yr

The Role As a Senior Machine Learning Engineer at Striveworks, you'll be challenged-and trusted-on ... Opportunities to conduct mission-critical field work This position offers a fully remote work ...

Machine Learning Lead

Austin, TX ยท On-site +1

$54.75 - $75/hr

Remote US (Bay Area, Austin preferred) About Autolane Autolane is on a mission to revolutionize ... The Role As Machine Learning Lead at Autolane, you'll architect and build the AI brain that ...

The Role As a Staff Machine Learning Engineer at Striveworks, you will be challenged-and trusted-on ... This position offers a fully remote work environment, or you can work hybrid/on site at our office ...

Software Engineer, Machine Learning Responsibilities: * Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences * Implement ...

next page

Showing results 1-20

Remote Machine Learning information

See Austin, TX salary details

$25.3K

$42.2K

$87.2K

How much do remote machine learning jobs pay per year?

As of May 28, 2026, the average yearly pay for remote machine learning in Austin, TX is $42,209.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

Is ML full of coding?

Machine Learning (ML) roles often involve significant coding, especially in programming languages like Python or R, to develop algorithms and models. However, some positions focus more on data analysis, feature engineering, or model evaluation, which may require less coding but still involve technical skills and understanding of ML concepts.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

What are the most commonly searched types of Machine Learning jobs in Austin, TX? The most popular types of Machine Learning jobs in Austin, TX are:
What job categories do people searching Remote Machine Learning jobs in Austin, TX look for? The top searched job categories for Remote Machine Learning jobs in Austin, TX are:
What cities near Austin, TX are hiring for Remote Machine Learning jobs? Cities near Austin, TX with the most Remote Machine Learning job openings:
Infographic showing various Remote Machine Learning job openings in Austin, TX as of May 2026, with employment types broken down into 2% Internship, 2% As Needed, 38% Full Time, 54% Part Time, 2% Temporary, and 2% Contract. Highlights an 73% Physical, and 27% Remote job distribution, with an average salary of $42,209 per year, or $20.3 per hour.

Machine Learning Engineer

Avride

Austin, TX โ€ข On-site, Remote

Other

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Machine Learning Engineer

Austin, TX

About the Team

Avride develops autonomous vehicle and delivery robot technology, leveraging deep expertise in autonomous systems. With the recent launch of our robotaxi service in Dallas, we are accelerating innovation and redefining the future of mobility.

Our team builds self-driving solutions from the ground up, with machine learning at the core of our development pipeline to enable safe and intelligent navigation. We design and deploy state-of-the-art models to address key challenges in autonomous systems, utilizing advanced deep learning architectures such as Convolutional Neural Networks (CNNs), Transformers, and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard applications, ensuring robust and efficient operation. Your work will directly contribute to enhancing the performance, safety, and reliability of Avride's autonomous vehicles and delivery robots.

About the Role

We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In this role, you will conduct experiments, manage large-scale datasets, and implement deep learning models tailored for autonomous systems. You will utilize cloud platforms, orchestration tools, and machine learning frameworks to develop scalable and efficient solutions. Additionally, you will analyze the latest research, assess the applicability of emerging deep learning techniques, and drive innovation in autonomous vehicle technology.

What You'll Do
  • 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.
What You'll Need
  • 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.
Nice to Have
  • 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.

Candidates are required to be authorized to work in the U.S. The employer is not offering relocation sponsorship, and remote work options are not available.

Avride is an equal opportunity employer and committed to providing reasonable accommodations to qualified applicants and employees with disabilities to ensure they have equal access to employment opportunities. Avride complies with the Americans with Disabilities Act (ADA), if you need a reasonable accommodation to assist with the application or hiring process, or to perform the essential functions of a job, please email jobs@avride.ai.