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Pytorch Developer Jobs in Prosper, TX (NOW HIRING)

Damco

AI/ML Engineer

Plano, TX

AI/ML Engineer Location: Plano, TX or Houston, TX or Morris Plains, NJ, (Hybrid) Duration: Contract ... Experience with machine learning libraries and frameworks, such as TensorFlow, PyTorch, scikit ...

Diverse Lynx

AI/ ML Engineer

Irving, TX

$120K - $125K/yr

AI/ML Engineer Location: Irving, TX Salary Range: $120,000 - $125,000 a year (plus full time ... Strong proficiency in PyTorch (preferred) or TensorFlow, and Python-based ML development. * Solid ...

WIS International

Principal Engineer AI

Plano, TX · On-site

Required : • 10+ years in software engineering or data science, with 5+ years specializing in AI/ML at enterprise scale. • Proven expertise in machine learning frameworks (TensorFlow, PyTorch ...

Resolve Tech Solutions

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 ...

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 ...

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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

ML / AI Engineer - MLOps & GenAI Platforms - AIRLHV

NavitasPartners

Dallas, TX • Hybrid

Full-time

Posted 12 days ago

Job description

ML / AI Engineer – MLOps & GenAI Platforms

Location: US / Canada (Remote/Hybrid)
Type: Contract / Full-Time

Overview:

We are seeking an ML/AI Engineer to contribute to large-scale AI and data transformation programs. This role focuses on building, deploying, and scaling machine learning and GenAI solutions in cloud environments.

Key Responsibilities:

  • Design and deploy scalable ML and GenAI solutions
  • Build and manage end-to-end MLOps pipelines
  • Collaborate with data engineers, architects, and business teams
  • Ensure model performance, governance, and lifecycle management

Required Skills:

  • Strong experience in ML/AI engineering and MLOps practices
  • Proficiency in Python and frameworks such as PyTorch
  • Experience with cloud platforms (AWS, Azure, GCP)
  • Hands-on experience with model deployment and monitoring

Nice to Have / Coverage:

  • Experience with LangChain and GenAI/agentic AI implementations
  • Exposure to Databricks, Snowflake, Azure Synapse, or BigQuery
  • Familiarity with AI governance, Responsible AI, and compliance frameworks
  • Experience working with cloud-native data platforms and architectures

For more details reach at resumes@navitassols.com.