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Tensorflow Pytorch Jobs in Washington, DC (NOW HIRING)

Redolent, Inc.

Sr, ML Architect

Washington, DC · On-site

Extensive experience with TensorFlow, PyTorch, and scikit-learn. * Cloud Platforms: Working knowledge of Google Cloud and Azure. * Design Tools: Proficiency in Figma, Adobe XD, or Sketch. * Databases:

Core Interface

Data Scientist

Chantilly, VA · On-site

Proficiency in Python , R , or Scala and strong knowledge of data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy). * Experience with cloud platforms (AWS, Azure, or GCP ...

Tecolote Research

Senior Data Scientist

Chantilly, VA · On-site

$130K - $160K/yr

The development of frameworks for creating and integrating machine learning models such as TensorFlow, Pytorch, Jupyter Notebook and or Apache Hadoop * The development and use of Visualizatin Tools ...

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). * Proficient with Databricks, MLflow, and PySpark. * Solid understanding of model ...

Steampunk

Data Scientist (Generative AI)

Mclean, VA

Demonstrated experience using AI frameworks like TensorFlow, PyTorch, Keras, or JAX. * Ability to implement and modify complex neural network architectures. * Skilled in using data manipulation and ...

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site

$140K - $150K/yr

Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). * Proficient with Databricks, MLflow, and PySpark. * Solid understanding of model ...

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Tensorflow Pytorch information

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$42.5K

$139K

$222.6K

How much do tensorflow pytorch jobs pay per year?

As of Jul 15, 2026, the average yearly pay for tensorflow pytorch in Washington, DC is $139,013.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,600.00 and $154,000.00 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 Washington, DC? For Tensorflow Pytorch jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Washington, DC look for? The top searched job categories for Tensorflow Pytorch jobs in Washington, DC are:
Tensorflow Pytorch jobs near you
Sr, ML Architect

Sr, ML Architect

Redolent, Inc.

Washington, DC • On-site

Contractor

Re-posted 29 days ago

Job description

Job Description:
We are seeking a highly skilled Senior ML Architect with extensive experience in designing and developing machine learning algorithms and deep learning applications, particularly for observability data (AIOps). The ideal candidate will have a strong background in time series forecasting, anomaly detection, event classification, and correlation ML algorithms. Additionally, experience in integrating with large language models (LLMs) and generative AI (GenAI) for effective summarization and other applications is essential.
Key Responsibilities:
  • Architect and design advanced machine learning algorithms for time series forecasting, anomaly detection, event classification, and correlation.
  • Develop and implement deep learning applications and systems for observability data (AIOps).
  • Integrate with large language models (LLMs) and generative AI (GenAI) using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques.
  • Implement MCP client and server within the Grafana ecosystem or similar platforms.
  • Collaborate with cross-functional teams to ensure seamless integration and deployment of ML models.
  • Lead and mentor a team of engineers, both onshore and offshore.
  • Provide strategic guidance on AI/ML best practices and emerging technologies.

Required Skills and Experience:
  • Programming Languages: Proficiency in Python and R.
  • ML Frameworks: Extensive experience with TensorFlow, PyTorch, and scikit-learn.
  • Cloud Platforms: Working knowledge of Google Cloud and Azure.
  • Design Tools: Proficiency in Figma, Adobe XD, or Sketch.
  • Databases: Knowledge of MySQL, MongoDB, and PostgreSQL.
  • Server-Side Languages: Familiarity with Python, Node.js, and Java.
  • Version Control: Experience with Git and other version control systems.
  • Testing: Knowledge of testing frameworks and methodologies.
  • Agile Development: Experience with agile development methodologies.
  • Communication and Collaboration: Strong communication and collaboration skills.
  • GenAI Experience: Proven experience in integrating and leveraging generative AI models for various applications, including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
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About Redolent

Sourced by ZipRecruiter

Redolent, a dynamic and rapidly expanding company committed to excellence in software solutions, where success is fueled by a combination of technical expertise and efficient management practices. Our solutions create a measurable delta in our clients’ productivity and profitability, contributing to their growth and success.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

San Jose, CA, US

Year founded

2008

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