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Pytorch Developer Jobs in Pearland, TX (NOW HIRING)

LLM Infrastructure Engineer

Houston, TX · On-site

$97K - $127K/yr

Build and deploy LLM inference services using HuggingFace Transformers and PyTorch * Optimize GPU ... A hands-on engineer who understands how LLM systems run in production-from model loading and ...

Strong programming experience in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn . * Experience in applying AI within engineering domains such as QA, DevOps, or ...

Strong programming experience in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn . * Experience in applying AI within engineering domains such as QA, DevOps, or ...

Lead AI Developer

Houston, TX · On-site

$90K - $110K/yr

Strong programming experience in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn . * Experience in applying AI within engineering domains such as QA, DevOps, or ...

As an AI/ML Full Stack Engineer at Calpine Inc., you will contribute to the development of AI ... Familiaritywith AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) andgenerative AI ...

Senior AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Expertise in AI/ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and the end-to ... Strong programming skills in Python and proficiency with relevant libraries (e.g., NumPy, Pandas ...

Engineer

Houston, TX · On-site

$100K - $150K/yr

As an Engineer in the Information industry, you will play a pivotal role in designing and ... Experience with machine learning frameworks such as TensorFlow or PyTorch. * Familiarity with ...

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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 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 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 popular job titles related to Pytorch Developer jobs in Pearland, TX? For Pytorch Developer jobs in Pearland, TX, the most frequently searched job titles are:
What job categories do people searching Pytorch Developer jobs in Pearland, TX look for? The top searched job categories for Pytorch Developer jobs in Pearland, TX are:
What cities near Pearland, TX are hiring for Pytorch Developer jobs? Cities near Pearland, TX with the most Pytorch Developer job openings:

LLM Infrastructure Engineer

AMSYS Talent

Houston, TX • On-site

$97K - $127K/yr

Full-time

Posted 9 days ago


Job description

We are looking for a Senior Python / AI API Engineer to build and deploy production-grade services powering Large Language Model (LLM) applications. This role focuses on developing high-performance APIs for model inference, optimizing GPU workloads, and deploying AI services in cloud environments.
This is an engineering-focused role, not research. We are looking for someone who has built and shipped AI systems into production and understands the challenges of scalable inference and model serving.
Key Responsibilities
  • Develop high-performance APIs using Python (3.10+) and FastAPI
  • Build and deploy LLM inference services using HuggingFace Transformers and PyTorch
  • Optimize GPU workloads and CUDA memory usage
  • Implement streaming inference APIs for real-time model responses
  • Containerize and deploy services using Docker and GPU-enabled infrastructure
  • Deploy AI workloads in Azure environments (AKS, ACI, or Container Apps)

Required Skills
  • Strong Python development experience (3.10+)
  • Hands-on experience building production APIs with FastAPI
  • Experience with HuggingFace Transformers and PyTorch
  • Solid understanding of REST API design
  • Experience deploying containerized applications with Docker

Nice to Have
  • Experience with OpenAI-compatible APIs, vLLM, or Text Generation Inference (TGI)
  • Experience deploying AI workloads on Azure GPU infrastructure
  • Familiarity with LoRA / PEFT fine-tuning
  • Exposure to legal or financial NLP use cases

Ideal Candidate: A hands-on engineer who understands how LLM systems run in production-from model loading and tokenization to GPU deployment and scalable APIs.