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Pytorch Developer Jobs in Frisco, TX (NOW HIRING)

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit ... GCP Professional Machine Learning Engineer certification is required. Experience with version ...

SAP AI Lead Developer

Plano, TX · On-site +1

$56.50 - $74/hr

... PyTorch, Scikit-learn), and programming languages (Python, R). • Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. • Strong architectural design and system integration skills ...

SAP AI Lead Developer

Plano, TX · On-site

$56.50 - $74/hr

... PyTorch, Scikit-learn), and programming languages (Python, R). • Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. • Strong architectural design and system integration skills ...

Develop and optimize machine learning and deep learning models using frameworks like TensorFlow or PyTorch. * Strong skills in programming languages such as Python, R, or Java, essential for ...

SAP AI Lead Developer

Plano, TX · On-site +1

$56.50 - $74/hr

Proficiency with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn), and programming languages (Python, R). Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. Strong ...

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

... PyTorch, or scikit-learn. • Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning. • ...

The Ops Emerging Technology Developer will research, plan, lead, develop, and implement solutions ... Experience with AI/ML or AIenabled solutions, frameworks, or services (e.g., TensorFlow, PyTorch ...

Showing results 41-60

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

Senior ML Engineer

Resolve Tech Solutions

Addison, TX • On-site

$101K - $138K/yr

Full-time

Re-posted 3 hours ago


Job description

Responsibilities:
Develop machine learning models and algorithms to address business needs.
Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions.
Clean, preprocess, and analyze large datasets to extract meaningful insights.
Deploy machine learning models into production environments and monitor their performance.
Continuously improve model accuracy and performance through experimentation and optimization.
Stay up-to-date with the latest advancements in machine learning and related technologies.
Communicate findings and results to stakeholders in a clear and concise manner.


Requirements:
Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field.
2~5 years of experience in machine learning, data science, or a related field.
Proficiency in programming languages such as Python, Java, or Scala.
Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
Experience with cloud platforms such as Google Cloud Platform (GCP), including services like BigQuery, Cloud Storage, and AI Platform.
GCP Professional Machine Learning Engineer certification is required.
Experience with version control systems such as Git.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills.


Preferred Qualifications:
Master's degree or higher in Computer Science, Engineering, Mathematics, or a related field.
Experience with distributed computing frameworks such as Apache Spark.
Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau.
Experience with natural language processing (NLP) or computer vision (CV) techniques.
Experience with continuous integration and continuous deployment (CI/CD) pipelines.
Contributions to open-source projects or participation in relevant communities.