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Pytorch Developer Jobs in Kansas City, MO (NOW HIRING)

We are seeking an AI Engineer II - Translation that will design and optimize machine learning ... Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face). * Experience with ...

... PyTorch, etc. 3 plus years of experience in building use cases / solutions especially around AI/ML cognitive services, based on Cloud infrastructure and services such as Azure cloud platforms and On ...

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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.

Research Engineer / Robotics / ML

Motion Recruitment

Lenexa, KS • On-site

Full-time

Re-posted 6 days ago


Job description

A robotics and AI team in Kansas is looking for a Research Engineer to help build the systems that power real world machine learning. This is a full-time role where you will be working across robotics, computer vision, and applied ML, using tools like ROS/ROS2, Python, C++, and PyTorch/TensorFlow.
Robots are out in the real-world collecting data, and your job is to help make sure that data is usable, structured, and feeding into machine learning models in the right way. If you are early in your career and want real exposure to robotics, ML and data systems all in one place, this is a rare setup.
Required Skills & Experience
  • 1-2 years of experience with robotics and machine learning (Internship experience acceptable)
  • Graduated with a bachelor’s degree in Computer Science
  • Experience with ROS/ROS2 frameworks
  • Proficiency in Python and C++
  • Worked with ML models (PyTorch/TensorFlow/ sklearn)
  • Experience working with data pipelines or making raw data usable for AI systems
Desired Skills & Experience
  • Exposure to robotic manipulators or mobile robot systems
  • Experience with biometric/ identity verification systems
  • Familiarity with cloud platforms
What You Will Be Doing
Tech Breakdown
  • 40% Robotics Systems
  • 35% Machine Learning
  • 25% Data Engineering
Daily Responsibilities
  • 50% Hands On
  • 30% Team Collaboration
  • 20% Systems improvement

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.