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Pytorch Developer Jobs in Austin, TX (NOW HIRING)

Java AI Engineer-C2C

Austin, TX · On-site

$51.25 - $70.50/hr

Java AI Engineer-NO OPT and H1B Location: Austin, TX/ Sunnyvale, CA (Sunnyvale - 2 Positions ... Familiarity with AI frameworks and libraries (e.g., TensorFlow, PyTorch, OpenCV)

Expert AI Engineer

Austin, TX · On-site

$147K - $210K/yr

Strong programming skills in Python, TensorFlow, PyTorch, and other AI frameworks. * Strong problem-solving skills with the ability to translate business challenges into AI-driven solutions. What we ...

... PyTorch) or scientific computing. • Experience with DevOps tools (Docker, Kubernetes, CI/CD pipelines) Company : Allen Control Systems develops autonomous defense technologies designed to detect ...

... PyTorch) or scientific computing. • Experience with DevOps tools (Docker, Kubernetes, CI/CD pipelines) Company : Allen Control Systems develops autonomous defense technologies designed to detect ...

We are looking for a GenAI Ops Engineer to train, fine-tune, and deploy Generative AI models (LLMs ... Train and fine-tune LLMs using PyTorch, DeepSpeed, and LoRA. * Optimize inference using ONNX, vLLM ...

... PyTorch) or scientific computing. • Experience with DevOps tools (Docker, Kubernetes, CI/CD pipelines) Company : Allen Control Systems develops autonomous defense technologies designed to detect ...

Staff Compiler Engineer

Austin, TX · On-site

$250K - $315K/yr

Integrate with existing ML frameworks (e.g., PyTorch, JAX, Triton). * Build and maintain test ... Programming Languages: Python and C (essential), Assembly * Compiler Frameworks: LLVM, MLIR, GCC ...

Lead Generative AI Data Engineer III

Austin, TX · On-site

$101K - $133K/yr

Our Deloitte AI & Engineering team works to transform technology platforms, drive innovation, and ... Active certification or advanced certification in Python, Pyspark, Pytorch, and Tensorflow.

Our Deloitte AI & Engineering team works to transform technology platforms, drive innovation, and ... Active certification or advanced certification in Python, Pyspark, Pytorch, and Tensorflow.

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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 cities near Austin, TX are hiring for Pytorch Developer jobs? Cities near Austin, TX with the most Pytorch Developer job openings:

Java AI Engineer-C2C

Kaav Inc

Austin, TX • On-site

$51.25 - $70.50/hr

Contractor

Posted 6 days ago


Job description

Job Title: Java AI Engineer-NO OPT and H1B

Location: Austin, TX/ Sunnyvale, CA (Sunnyvale – 2 Positions, Austin – 3 Positions) – Locals Only.

NO OPT and H1B

Experience Level: 5–10 Years

Key Responsibilities:

Design, develop, and maintain scalable Java-based applications.

Collaborate with cross-functional teams to integrate AI and ML components into full-stack solutions.

Participate in code reviews, testing, and deployment processes.

Research and prototype AI-driven features to enhance product capabilities.

Optimize application performance and ensure high availability.

Required Skills:

Core Java: 5–10 years of hands-on experience.

Full Stack Java Development: 5–10 years

Strong understanding of software engineering principles and design patterns.

Artificial Intelligence: 2–5 years

Machine Learning: 2–5 years of experience in building or integrating ML models.

Familiarity with AI frameworks and libraries (e.g., TensorFlow, PyTorch, OpenCV).