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Pytorch Developer Jobs (NOW HIRING)

cyberThink, Inc.

AI Developer

San Jose, CA

Implement machine learning models (using frameworks like PyTorch, TensorFlow, or scikit-learn) into web and mobile applications. Backend & API Engineering: Build and maintain scalable backend ...

BravoTech

Sr AI Developer

Irving, TX · On-site

$112K - $151K/yr

PyTorch / TensorFlow / Scikit-learn * LangChain / OpenAI APIs / Hugging Face * MLOps & CI/CD * Azure, AWS, or GCP * RAG Architectures & AI Agents * Cloud AI Deployment * Data Engineering Fundamentals ...

Purple Drive Technologies

Python Developer

Tampa, FL · On-site

$47.50 - $65.50/hr

Job Title: Python AI/ML Engineer - AI & Automation Location: Tampa, FL (Local candidates only ... Hands-on expertise with TensorFlow, PyTorch, or Scikit-Learn . * Strong understanding of ...

Atika Tech

Gen AI Developer / Sr.

Irving, TX

$116K - $157K/yr

Position: Gen AI Developer / Sr. Location: Irving, TX Type: Fulltime No. of Positions: Multiple ... Proficiency in Python and experience with AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face)

Elite WorkForce Inc

PA · On-site

Artificial Intelligence Developer Location: Dauphin County, PA (Online Locals Preferred) Client ... Hands-on experience with machinae learning frameworks (PyTorch, TensorFlow). * Familiarity with OCR ...

Capgemini

AI Solutions Developer

Tampa, FL · On-site

$47.50 - $65.50/hr

Design build and optimize machine learning and deep learning models using PyTorch TensorFlow and ... Work closely with product engineering and business teams to translate strategic requirements into ...

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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.
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Pytorch Developer jobs near you
Infographic showing various Pytorch Developer job openings in the United States as of May 2026, with employment types broken down into 84% Full Time, 3% Part Time, and 13% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution.

Machine Learning Developer

Futran Tech Solutions Pvt. Ltd.

Remote

Full-time

Posted 24 days ago

Job description

ML Engineer
Preferred location - Seattle USA
Skillsets:
Must have:
Azure Machine Learning - building , training, testing models
Python Programming & associated libraries (scikit learn, PyTorch, TensorFlow etc)
Nice to have:
Understanding of ML algorithms, frameworks and libraries, statistical modeling, and predictive analytics techniques.
Knowledge of open source model repositories like hugging face.
Knowledge of inference runners for evaluating model performance.
Develop and maintain the machine learning system and platform, including training, inference, pipeline orchestration.
Knowledge on Azure ML SDK or the Azure ML Studio.

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