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Pytorch Developer Jobs in Alexandria, VA (NOW HIRING)

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 ...

Parsons

Software Developer - TS/SCI

Herndon, VA

Parsons Corporation is currently searching for a full-time Software Developer Mid Level position at ... Machine learning framework experience (PyTorch, Tensorflow) * Docker/containerization experience

Polar IT Services

AWS Python Developer

Reston, VA · Hybrid

$52.25 - $72/hr

... 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.

Polar IT Services

AWS Python Developer

Reston, VA · On-site

$52.25 - $72/hr

... 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.

Polar IT Services

AWS Python Developer

Reston, VA · Hybrid

$52.25 - $72/hr

... 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.

Parsons

Senior Software Developer - TS/SCI

Herndon, VA · On-site

$56 - $74/hr

Software Developer position at our Chantilly, VA location. This will lead teams in the design ... Machine learning framework experience (PyTorch, Tensorflow) * Docker/containerization experience

Parsons

Junior Software Developer - TS/SCI

Chantilly, VA

$68K - $89K/yr

Parsons Corporation is currently searching for a full-time Software Developer Junior position at ... Machine learning framework experience (PyTorch, Tensorflow) * Docker/containerization experience

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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 Alexandria, VA? For Pytorch Developer jobs in Alexandria, VA, the most frequently searched job titles are:
What job categories do people searching Pytorch Developer jobs in Alexandria, VA look for? The top searched job categories for Pytorch Developer jobs in Alexandria, VA are:
What cities near Alexandria, VA are hiring for Pytorch Developer jobs? Cities near Alexandria, VA with the most Pytorch Developer job openings:
Pytorch Developer jobs near you
AI Platform Developer

AI Platform Developer

Staffingine LLC

Herndon, VA • On-site

Contractor

Posted 12 days ago

Job description

Job Title: Sr. AI Platform Developer
Job Location: Herndon, VA
Job Type: Contract

Job Description:

  1. Programming Languages: Mastery of Python is essential, with R, Java, and C++ also being highly valuable.
  2. Machine Learning (ML) & Deep Learning (DL): You'll need a deep understanding of ML concepts (supervised, unsupervised, reinforcement learning) and neural network architectures like CNNs and RNNs.
  3.  AI/ML Frameworks and Libraries: Proficiency is required in tools like TensorFlow, PyTorch, Keras, and scikit-learn.
  4. Data Science and Analysis: Skills in data acquisition, cleaning, preprocessing, and feature engineering are crucial, along with knowledge of SQL and NoSQL databases.
  5.  Big Data Technologies: Familiarity with platforms like Apache Spark and
  6. OpenSearch is often necessary for handling large-scale data.
  7. Mathematics and Statistics: A strong foundation in linear algebra, calculus, probability, and statistics is fundamental.
  8. Natural Language Processing (NLP): For language-based AI, expertise in NLP techniques and libraries such as NLTK, spaCy, and Hugging Face Transformers is key.
  9. Cloud Computing and MLOps: Knowledge of cloud platforms (AWS, GCP, Azure) and
  10. MLOps principles is vital for deploying and managing AI models.