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Pytorch Developer Jobs in Frisco, TX (NOW HIRING)

IT America Inc

ML Engineer

Plano, TX · On-site

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 ...

NTT DATA Services

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 ...

NTT DATA Services

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 ...

NTT DATA Services

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 ...

Resolve Tech Solutions

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. • ...

FedEx Office

Ops Emerging Tech Developer

Plano, TX · Hybrid

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 ...

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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 Frisco, TX? For Pytorch Developer jobs in Frisco, TX, the most frequently searched job titles are:
What job categories do people searching Pytorch Developer jobs in Frisco, TX look for? The top searched job categories for Pytorch Developer jobs in Frisco, TX are:
What cities near Frisco, TX are hiring for Pytorch Developer jobs? Cities near Frisco, TX with the most Pytorch Developer job openings:
Pytorch Developer jobs near you
ML Engineer

ML Engineer

IT America Inc

Plano, TX • On-site

Contractor

Re-posted 24 days ago

Job description

Position: ML Engineer

Location: Plano, TX / Reston, VA (Hybrid)

Duration: Long term contract

Interview: Onsite

Top Skills' Details:

1. Strong Python and AWS skills

2. Machine Learning, LLM, GenAi experience

3. Needs to be a hands on engineer (this means the person has to be a coder/programmer)

Job Description:

  • 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 developing AI applications.
  • Build and maintain AI pipelines, from data processing to model deployment.
  • Analyze complex datasets to uncover insights and improve model performance.
  • Ability to analyze complex problems and develop effective AI-driven solutions.
  • Deploy AI solutions on cloud platforms such as AWS.
  • Collaborate with technical and business teams to identify AI opportunities and deliver impactful solutions.
  • Deep understanding of deploying AI applications within a CICD environment, specifically AWS.

Preferred Qualifications:

  • Experience with MLOps tools (e.g., MLflow, Kubeflow).
  • Knowledge of big data technologies (Spark, Hadoop, Databricks).
  • Background in NLP, computer vision, or other advanced AI techniques.
  • Relevant certifications (Coursera, edX, AWS, Azure, Google Cloud).

Required qualifications:

  • Strong programming skills in Python, R, or Java.
  • Hands-on experience with machine learning algorithms and frameworks.
  • Familiarity with major cloud platforms for AI deployment.
  • Strong analytical and problem solving skills.
  • Solid foundation in mathematics and statistics