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Tensorflow Pytorch Jobs in Seattle, WA (NOW HIRING)

Connexions Data Inc

Gen AI Developer

Seattle, WA · On-site

$57.25 - $78.75/hr

Must Have Technical/Functional Skills Experience in executing projects in Agile Framework Proven experience in machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch). Strong ...

Staffingine LLC

Artificial Intelligence Engineer

Bellevue, WA · On-site

$129K - $155K/yr

Experience with ML frameworks eg scikitlearn XGBoost TensorFlow PyTorch. * Strong knowledge of statistics experimental design and causal inference. * Handson experience with data visualization tools ...

Amazon

Senior Machine Learning Compiler Engineer

Seattle, WA

$139K - $183K/yr

... PyTorch, TensorFlow and MxNet. Amazon Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments. The ...

Amazon

Senior Machine Learning Compiler Engineer

Seattle, WA · On-site

$139K - $183K/yr

... PyTorch, TensorFlow and MxNet. Amazon Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments. The ...

Zortech Solutions

MLOps Engineer

Bellevue, WA · Remote

... Tensorflow, PyTorch, HuggingFace Transformers and libraries (like scikit-learn, etc.). * 4-6 years of experience with ClassicAI/GenAI ML Model Operationalization in Production. * 4 to 6 years of ...

Nvidia

Senior Software Engineer, AI Networking

Seattle, WA

$139K - $183K/yr

Proficiency in building and using ML models with leading frameworks such as PyTorch or TensorFlow, or JAX. * Proven ability to apply GNNs/transformers-based optimization to PyTorch model graph and ...

Qualtrics

Staff Applied Scientist

Seattle, WA · On-site

TensorFlow, PyTorch, MXNet etc) * Preference for a publication record in top-tier ML and NLP conferences (e.g. NeurIPS, ICML, SIGIR, ICLR, ACL, EMNLP, etc.) * Proven track record in evaluating ...

Qualtrics

Staff Applied Scientist

Seattle, WA

TensorFlow, PyTorch, MXNet etc) * Preference for a publication record in top-tier ML and NLP conferences (e.g. NeurIPS, ICML, SIGIR, ICLR, ACL, EMNLP, etc.) * Proven track record in evaluating ...

Kanak Elite Services Inc

Sr ML Platform Manager

Seattle, WA · On-site

$144K - $190K/yr

Proficiency in programming languages such as Python, R, or Java; experience with machine learning frameworks (TensorFlow, PyTorch, etc.); strong understanding of data engineering principles. MLOps ...

Qualtrics

Applied Scientist II

Seattle, WA · On-site

Show strong programming skills in languages like Python, along with proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar. How You'll Grow * Passion for leveraging cutting ...

Amazon

Senior Machine Learning Compiler Engineer

Seattle, WA · On-site

$139K - $183K/yr

More specifically, the Amazon Neuron team is developing a deep learning compiler stack that takes neural network descriptions created in frameworks such as TensorFlow, PyTorch, and MXNET, and ...

Intac Solution

Network Tester

Bellevue, WA

$34 - $36/hr

Proficiency in AI/ML platforms and APIs (e.g., OpenAI, TensorFlow, PyTorch, Hugging Face, Azure AI Studio). * Detect and track software defects and inconsistencies; analyzing the testing results and ...

Union.ai

Staff Software Engineer

Bellevue, WA · On-site

... TensorFlow, PyTorch, and Spark • 6 years of experience bridging traditional software development with cutting-edge ML applications • 6 years of experience utilizing Python Internals • 6 years ...

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All JobsTensorflow Pytorch JobsTensorflow Pytorch Jobs in Seattle, WA

Tensorflow Pytorch information

See Seattle, WA salary details

$42.7K

$139.7K

$223.6K

How much do tensorflow pytorch jobs pay per year?

As of Jul 30, 2026, the average yearly pay for tensorflow pytorch in Seattle, WA is $139,680.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,100.00 and $154,800.00 per year, depending on experience, location, and employer.

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.
What are popular job titles related to Tensorflow Pytorch jobs in Seattle, WA? For Tensorflow Pytorch jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Seattle, WA look for? The top searched job categories for Tensorflow Pytorch jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Tensorflow Pytorch jobs? Cities near Seattle, WA with the most Tensorflow Pytorch job openings:
Tensorflow Pytorch jobs near you
Infographic showing various Tensorflow Pytorch job openings in Seattle, WA as of July 2026, with employment types broken down into 43% Internship, and 57% Full Time. Highlights an 100% In-person job distribution, with an average salary of $139,680 per year, or $67.2 per hour.

Gen AI Developer

Connexions Data Inc

Seattle, WA • On-site

$57.25 - $78.75/hr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Must Have Technical/Functional Skills
Experience in executing projects in Agile Framework
Proven experience in machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch).
Strong programming skills in Python and familiarity with libraries such as NumPy, Pandas, and Scikit-learn.
Experience with generative models (e.g., GANs, VAEs, Transformers) and natural language processing.
Proficiency in RAG (Retrieval-Augmented Generation) techniques.
Strong understanding of natural language processing (NLP). Experience with data preprocessing and model fine-tuning.
Familiarity with evaluation metrics for RAG systems.
Knowledge of transformer architectures and training techniques.
Awareness of ethical considerations and bias mitigation strategies.
Understanding of autonomous decision-making algorithms.
Proficiency in programming language Python.
Strong analytical and problem-solving skills.
Roles & Responsibilities
Qualifications:
Bachelor s or master s degree in computer science, data science or equivalent
Develop and implement generative AI models using frameworks like TensorFlow and PyTorch.
Build and optimize RAG (Retrieval-Augmented Generation) pipelines.
Work on NLP tasks such as text classification, summarization, and conversational AI.
Perform data preprocessing, cleaning, and feature engineering using Python libraries (NumPy, Pandas).
Fine-tune and optimize transformer-based models and LLMs for specific use cases.
Evaluate model performance using RAG and NLP evaluation metrics.
Develop and integrate machine learning models into applications.
Apply autonomous decision-making logic in AI-driven workflows where needed.
Generic Managerial Skills, If any
Good to have Manufacturing domain understanding
Excellent communication
Team collaboration
Documentation and knowledge sharing

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