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Tensorflow Pytorch Jobs in Washington (NOW HIRING)

Saxon Global

Platform Developer

Herndon, VA · On-site

Hands-on experience with TensorFlow, PyTorch, Keras, and scikit-learn. Experience with data processing, SQL and NoSQL databases. Familiarity with Apache Spark and large-scale data processing. Solid ...

VTG

Data Scientist

Mclean, VA · On-site

Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) * Strong foundation in statistics, probability, and data analysis techniques * Experience with SQL and working ...

VTG

Data Scientist

Herndon, VA

Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) * Strong foundation in statistics, probability, and data analysis techniques * Experience with SQL and working ...

Saxon Global

Platform Developer

Reston, VA

Hands-on experience with TensorFlow, PyTorch, Keras, and scikit-learn. * Experience with data processing, SQL and NoSQL databases. * Familiarity with Apache Spark and large-scale data processing.

VTG

Data Scientist

Chantilly, VA

Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) * Strong foundation in statistics, probability, and data analysis techniques * Experience with SQL and working ...

Staffingine LLC

AI Platform Developer

Herndon, VA · On-site

Proficiency is required in tools like TensorFlow, PyTorch, Keras, and scikit-learn. * Data Science and Analysis: Skills in data acquisition, cleaning, preprocessing, and feature engineering are ...

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Tensorflow Pytorch information

What are the key skills and qualifications needed to thrive as a Deep Learning Engineer specializing in TensorFlow and PyTorch, and why are they important?

To thrive as a Deep Learning Engineer with a focus on TensorFlow and PyTorch, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree. Proficiency in programming languages like Python, experience with TensorFlow and PyTorch frameworks, and familiarity with cloud platforms or GPU computing are essential. Analytical thinking, problem-solving, and effective communication are standout soft skills for collaborating with teams and interpreting model results. These skills are crucial for developing, deploying, and optimizing AI models that drive innovation and solve complex real-world problems.

What are TensorFlow and PyTorch?

TensorFlow and PyTorch are two of the most popular open-source deep learning frameworks used by researchers and developers to build, train, and deploy machine learning models. TensorFlow, developed by Google, offers robust support for production environments and has a large ecosystem. PyTorch, developed by Facebook, is known for its flexibility, ease of use, and dynamic computational graph, making it popular in academia and research. Both frameworks support a wide range of neural network architectures and are used extensively for tasks such as computer vision, natural language processing, and reinforcement learning.

What is the difference between Tensorflow Pytorch vs Data Scientist?

AspectTensorflow PytorchData Scientist
Required SkillsDeep learning frameworks, Python, machine learningData analysis, statistical skills, Python/R, machine learning
Work EnvironmentAI/ML development, research, software engineeringData analysis, reporting, business insights
Industry UsageAI/ML projects, research labs, tech companiesBusiness, finance, healthcare, tech

Tensorflow and Pytorch are deep learning frameworks used primarily by AI/ML developers, while Data Scientists utilize these tools for data analysis and modeling. Although their skill sets overlap, Tensorflow Pytorch focus on model development, whereas Data Scientists apply these models to derive insights and inform decisions.

How do TensorFlow/PyTorch engineers typically collaborate with data scientists and other team members in a production environment?

TensorFlow and PyTorch engineers often work closely with data scientists to transform experimental machine learning models into efficient, scalable production solutions. Collaboration involves frequent code reviews, shared development environments, and regular meetings to align model requirements with deployment constraints. Engineers also coordinate with DevOps teams to ensure smooth integration and monitoring of models in production. Strong communication skills and a willingness to iterate on solutions are essential for bridging the gap between research and real-world application.
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Tensorflow Pytorch jobs near you
Senior AI/ML Developer with Security Clearance

Senior AI/ML Developer with Security Clearance

MasterPeace Solutions, Ltd.

Fort George G Meade, MD

Other

Posted 5 days ago

Job description

Qualifications: • Bachelor's degree plus 8-years of experience
• Python (i.e. SciKit-learn, TensorFlow, PyTorch), • R
• GIT
• Jupyter Notebooks. • Relational Database Management (with TensorFlow) Desired: proficiency in augmenting, providing context, and/or fine-tuning large language models for generative tasks using approaches such as but not limited to, retrieval augmented generation (RAG) and model context protocol (MCP).

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