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Deep Learning Developer Jobs in Texas (NOW HIRING)

Avride

Senior / Staff Machine Learning Engineer

Austin, TX

$124K - $171K/yr

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 ...

Avride

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

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 ...

Avride

Machine Learning Engineer

Austin, TX · On-site

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 ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

SIMILAR CAREER TITLES Data Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML ...

Cymertek

Machine Learning Engineer

San Antonio, TX

SIMILAR CAREER TITLESData Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML Researcher ...

Cisco

Principal Machine Learning Engineer

Austin, TX · On-site

The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the ... Preferred : • Deep NLP & Domain‑Adapted LLMs: Background in building and adapting large‑scale ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We are looking for an experienced Senior Machine Learning Engineer with deep expertise in statistical and machine learning techniques, large-scale data processing, and model deployment in cloud ...

Roku

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

We're looking for strong engineers well versed with modern large scale machine learning platforms ... Building SOTA Deep learning discriminative models and build generative models to generate image and ...

CesiumAstro

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 ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We are looking for an experienced Senior Machine Learning Engineer with deep expertise in statistical and machine learning techniques, large-scale data processing, and model deployment in cloud ...

TalentPros.AI

Staff Machine Learning Engineer

Austin, TX

$120K - $550K/yr

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

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Deep Learning Developer information

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

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 are Deep Learning Developers?

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.

Which 3 jobs will survive AI?

Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other resilient roles include AI ethicists, who address ethical considerations, and AI system trainers, who curate and annotate data to improve AI performance. These jobs involve complex problem-solving and human oversight that are less easily automated.

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 in Texas are hiring for Deep Learning Developer jobs? Cities in Texas with the most Deep Learning Developer job openings:
Deep Learning Developer jobs near you
Infographic showing various Deep Learning Developer job openings in Texas as of May 2026, with employment types broken down into 37% Full Time, 57% Part Time, 5% Contract, and 1% Nights. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution.

Machine Learning Engineer, Motion Planning & Prediction

Avride

Austin, TX

$113K - $136K/yr

Other

Posted 7 days ago

Job description

About the Team

Our team develops the core software and data processing systems that power motion planning and decision-making in autonomous vehicles. We work at the intersection of machine learning, large-scale data infrastructure, and real-time vehicle control, collaborating across engineering, analytics, and product teams to deliver safe and intelligent driving capabilities.

About the Role

We are looking for a creative & driven Machine Learning Engineer to join our autonomous vehicle team. You will be at the center of our efforts to build intelligent systems that can understand, predict, and safely navigate a complex and dynamic world. This role involves designing and training the next generation of deep learning models that form the brain of our vehicle, learning from petabytes of real-world driving data. If you are passionate about applying cutting-edge ML to solve high-stakes robotics challenges, we want to hear from you.

What You'll Do
  • Design, train, and deploy state-of-the-art machine learning models for behavioral prediction and motion planning
  • Develop robust data pipelines to process, clean, and label massive-scale vehicle sensor and simulation datasets
  • Work with deep learning architectures such as transformers to model complex temporal interactions between traffic agents
  • Establish and own the metrics for model performance, and create evaluation frameworks that correlate with on-road safety and performance
  • Collaborate with software engineers to integrate and optimize trained models for real-time inference on the vehicles embedded hardware
  • Stay current with the latest research in machine learning, imitation learning, and reinforcement learning, and apply novel techniques to our systems
What You'll Need
  • Strong proficiency in Python and hands-on experience with modern deep learning frameworks (e.g., PyTorch, TensorFlow, or JAX)
  • Solid understanding of machine learning fundamentals, including various neural network architectures, training methodologies, and evaluation techniques
  • Experience with the full machine learning lifecycle, from data exploration and prototyping to deployment and monitoring
  • Proficiency in C++ for writing high-performance model inference code
Nice to Have
  • A strong track record in ML competitions (e.g., Kaggle) or contributions to major open-source ML projects
  • Experience applying ML to problems in robotics, such as behavioral prediction, motion planning, or computer vision
  • Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, Weights & Biases)
  • Experience with large-scale distributed data processing and training frameworks (e.g., Spark, Ray)
  • Publications in top-tier ML or robotics conferences (e.g., NeurIPS, ICML, CVPR, ICLR, CoRL, RSS)

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