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Deep Learning Developer Jobs in Austin, TX (NOW HIRING)

About the team Avride develops autonomous vehicle and delivery robot technology, leveraging deep ... About the role We are hiring experienced Machine Learning Engineers across Senior, Staff, and ...

Design, implement, and refine deep learning models to ensure efficiency, scalability, and ... Avride is a developer and operator of autonomous vehicles and delivery robots. Founded in 2017, the ...

* Senior Machine Learning Engineers needed for high growth tech company * Austin, TX - must be ... Familiarity with large-scale deep learning architectures used for recommendation or ranking systems ...

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

Design, implement, and refine deep learning models to ensure efficiency, scalability, and ... Avride is a developer and operator of autonomous vehicles and delivery robots. Founded in 2017, the ...

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

CesiumAstro is a developer and pioneer of communication systems for satellites and airborne ... Responsibilities : • Design, develop, and maintain deep learning pipelines for real-time data ...

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

CesiumAstro is a developer and pioneer of innovative communication systems for satellites and ... Responsibilities : • Design, develop, and maintain deep learning pipelines for real-time data ...

Demonstrated experience in deep learning and transformers models * Proficiency in frameworks like PyTorch or Tensorflow * Strong foundation in data structures, algorithms, and software engineering ...

You will be working with our engineering and product teams to design, build and productionize ... Keep track of emerging tech and trends, research the state-of-the-art deep learning models ...

Showing results 21-40

Deep Learning Developer information

See Austin, TX salary details

$17

$38

$50

How much do deep learning developer jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for deep learning developer in Austin, TX is $38.10, according to ZipRecruiter salary data. Most workers in this role earn between $32.40 and $42.40 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a deep learning developer?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What is a deep learning developer?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

What is the difference between Deep Learning Developer vs Machine Learning Engineer?

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges deep learning developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.
What cities near Austin, TX are hiring for Deep Learning Developer jobs? Cities near Austin, TX with the most Deep Learning Developer job openings:
Infographic showing various Deep Learning Developer job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $79,254 per year, or $38.1 per hour.

Senior / Staff Machine Learning Engineer

Avride

Austin, TX

$124K - $171K/yr

Full-time

Re-posted 12 days ago


Job description

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 hiring experienced Machine Learning Engineers across Senior, Staff, and Principal levels. to site onsite in Austin, Texas. Whether you're a strong individual contributor ready to take on complex technical challenges, or a seasoned technical leader looking to take on complex technical challenges we want to hear from you.
In this role, you will drive the development and deployment of machine learning solutions for some of the hardest problems in autonomy conducting experiments, managing large-scale datasets, and implementing deep learning models tailored for real-world autonomous systems. At more senior levels, you will also define technical strategy, mentor engineers, and influence how ML is practiced across the organization.

What you'll do
  • Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness - including models for environmental perception and predicting the behavior of other road users. At Staff and Principal levels, you will set the technical vision for entire model families and drive architectural decisions across teams.
  • Curate and Manage Large-Scale Datasets: Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation. Senior+ engineers will establish standards and tooling that scale across the organization.
  • Enhance and Maintain Training Pipelines: Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring. Staff and Principal engineers will own the long-term roadmap for training infrastructure.
  • Improve Model Deployment and Efficiency: Optimize inference performance, model compression, and deployment across various hardware platforms.
  • Explore and Apply Cutting-Edge ML Techniques: Stay current with advancements in deep learning and lead the evaluation and adoption of novel approaches. Principal engineers are expected to identify opportunities before they become industry standard.
  • Collaborate and Lead Across Teams: Work closely with researchers, software engineers, and robotics experts to integrate ML into real-world autonomous systems. At Staff and Principal levels, you will drive alignment across functions, mentor junior and senior engineers, and serve as a technical authority across the org.
What you'll need
  • Strong understanding of fundamental machine learning algorithms and neural network techniques.
  • Deep expertise in at least one modern ML domain, such as computer vision, large language models, or generative AI.
  • Senior: 4+ years of experience developing neural network-based algorithms, including data collection, training, and deployment.
  • Staff: 7+ years of experience, with a track record of leading significant technical initiatives and influencing engineering practices beyond your immediate team.
  • Principal: 10+ years of experience, with demonstrated impact at an organizational or industry level - setting multi-year technical direction and driving outcomes across multiple teams.
  • 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 from research papers, technical reports, and documentation.
  • Strong collaboration and communication skills, with the ability to align technical work with business objectives at all levels of the organization.
What you must 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.
  • Publications in top-tier ML conferences, contributions to patent applications, or ML-related open-source projects.
  • For Staff/Principal: experience building and scaling ML teams, defining org-wide technical standards, or driving cross-company research agendas