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Pytorch Developer Jobs in Webster, TX (NOW HIRING)

You would collaborate with software engineers, AI researchers, and hardware specialists to develop ... as PyTorch, ONNX, and TensorRT . * Experience with real-time embedded systems and handling large ...

... PyTorch, scikit-learn, or Azure AI services. * Software Engineering: Strong programming skills in ... Experience building and managing CI/CD pipelines, version control (Git), and DevOps practices ...

Senior ML/RL Engineer, Behavior Planning

Houston, TX · On-site

$99K - $137K/yr

... Engineer to develop their unified behavioral architecture. This role involves bridging the gap ... PyTorch; strong understanding of modern deep learning architectures and optimization techniques ...

... PyTorch, scikit-learn, or Azure AI services. * Software Engineering: Strong programming skills in ... Experience building and managing CI/CD pipelines, version control (Git), and DevOps practices ...

Aerospace Engineer

Houston, TX · On-site

$86K - $198K/yr

Experience applying machine learning (ML) to solve engineering problems with modern ML frameworks such as PyTorch or Tensorflow * Experience developing simulations using NVIDIA Warp and CUDA Python ...

Aerospace Engineer

Houston, TX · On-site +1

$86K - $198K/yr

Experience applying machine learning (ML) to solve engineering problems with modern ML frameworks such as PyTorch or Tensorflow * Experience developing simulations using NVIDIA Warp and CUDA Python ...

Experience applying machine learning (ML) to solve engineering problems with modern ML frameworks such as PyTorch or Tensorflow * Experience developing simulations using NVIDIA Warp and CUDA Python ...

AI Engineer

Houston, TX · On-site

$120 - $125/hr

AI Engineer Location: Houston, Texas Type: Direct Hire Salary: $120,000 - $125,000 Summary: The AI ... Strong Python skills, including experience with ML/AI frameworks (PyTorch, Hugging Face ...

SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

Strong programming proficiency in Python (5+ years) and deep experience with core ML/NLP libraries such as PyTorch, TensorFlow * Hands-on experience with LLM agent frameworks for building complex ...

Showing results 21-40

Pytorch Developer information

What is a PyTorch developer?

A PyTorch Developer is a software engineer or data scientist who specializes in using PyTorch, an open-source machine learning library, to build and deploy deep learning models. Their responsibilities typically include designing neural network architectures, training and evaluating models, and optimizing code for performance. PyTorch Developers work in fields such as artificial intelligence, computer vision, and natural language processing, collaborating with teams to solve complex problems using machine learning. They are proficient in Python and have a strong understanding of deep learning concepts. Additionally, they often contribute to research, development, and the deployment of AI solutions in production environments.

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

Pytorch Developers often encounter challenges when transitioning models from research to production, such as optimizing model performance for inference speed and memory usage, ensuring compatibility with deployment frameworks like TorchScript or ONNX, and managing dependencies across different systems. Additionally, integrating PyTorch models into existing software stacks and maintaining reproducibility can be complex. Collaborating closely with DevOps and data engineering teams is crucial to address these issues and ensure smooth deployment.

What are the key skills and qualifications needed to thrive as a PyTorch developer, and why are they important?

To thrive as a Pytorch Developer, you need strong programming skills in Python, a solid grasp of machine learning concepts, and experience with deep learning frameworks—especially PyTorch itself. Familiarity with tools like CUDA, Jupyter Notebooks, and version control systems (e.g., Git) is typically expected, along with knowledge of cloud platforms or relevant certifications. Problem-solving ability, effective collaboration, and clear communication are crucial soft skills for success in this role. These skills and qualities are vital for efficiently building, optimizing, and deploying machine learning models in real-world applications.

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

AspectPytorch DeveloperMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, experience with PyTorchBachelor's or higher in CS, data science, or related field, with ML experience
Work EnvironmentResearch labs, AI startups, tech companies focusing on deep learningTech companies, finance, healthcare, often involving deployment and scaling ML models
Industry UsagePrimarily in AI research and development teamsAcross industries implementing ML solutions in production

While both roles require knowledge of machine learning and experience with PyTorch, a Pytorch Developer mainly focuses on developing and optimizing deep learning models using PyTorch. A Machine Learning Engineer often has a broader scope, including deploying, maintaining, and scaling ML models across various platforms and industries.

What are popular job titles related to Pytorch Developer jobs in Webster, TX?

For Pytorch Developer jobs in Webster, TX, the most frequently searched job titles are:

What job categories do people searching Pytorch Developer jobs in Webster, TX look for?

The top searched job categories for Pytorch Developer jobs in Webster, TX are:

What cities near Webster, TX are hiring for Pytorch Developer jobs?

Cities near Webster, TX with the most Pytorch Developer job openings:

Senior Algorithm Engineer, Deep Learning & Vision

Socket.dev

Houston, TX • On-site

$150 - $210/hr

Other

Posted 29 days ago


Job description

Company Introduction

At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.


Key Responsibilities

  • Explore and propose new ideas using your knowledge and experience in deep learning, neural networks and large foundation models in autonomous driving including: end-to-end object detection, tracking and prediction, end-to-end planning and control, and end-to-end autonomous driving system, end-to-end online mapping. SLAM in localization and etc..

  • Work on the entire life cycle of machine learning projects from data analysis, model experimentations to performance metrics verifications, and understand the entire workflow in great detail.

  • Be exposed to many cross-team projects and collaborate with the product, simulation and other sibling autonomous driving algorithm teams to extend machine learning technology to all components.


Qualifications
Required:

  • Have an advanced degree (Ph.D or Master’s) in related fields of study: computer science, computer engineering, robotics, mathematics, physics, and etc.

  • Have in-depth knowledge and extensive experience in machine learning, and/or computer vision, modern transformer architecture, and employ SOTA techniques of machine learning.

  • Be familiar with PyTorch, TensorFlow and other machine learning platforms and tools.

  • Have strong motivation to work independently in a fast paced environment while collaborating with other teams on more complex and larger projects.


Preferred:

  • Have a proven track record of research publications in top conferences and/or journals as the first author.

  • Have knowledge and experience of generative models, model distillation, or model inference acceleration (e.g. TensorRT) techniques.

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