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Pytorch Developer Jobs in Pennsylvania (NOW HIRING)

Elite WorkForce Inc

PA · On-site

Artificial Intelligence Developer Location: Dauphin County, PA (Online Locals Preferred) Client ... Hands-on experience with machinae learning frameworks (PyTorch, TensorFlow). * Familiarity with OCR ...

Elite WorkForce Inc

PA · On-site

Strong programming skills in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch). * Proficiency in NLP tools (e.g., spaCy, Hugging Face, NLTK). * Hands-on experience with Microsoft ...

Siri InfoSolutions Inc

MLOPS Engineer

Malvern, PA · On-site

$50 - $60/hr

... MLOps, DevOps, or similar disciplines. * Knowledge in the life cycle management of Machine Learning models. * Proficiency with Machine Learning frameworks like TensorFlow, PyTorch, or Scikit-learn.

Acess Global

Sr ML Engineer

Malvern, PA · On-site

$102K - $140K/yr

Job Title: Sr ML Engineer Location: CITY - Malvern, PA Duration: 6 months Experience Required: 8-10 ... PyTorch / Scikit‑learn) Experience building scalable ML pipelines using SageMaker Pipelines ...

Comcast

Machine Learning Engineer 3-7881

Philadelphia, PA · On-site +1

$115K - $138K/yr

TensorFlow, PyTorch, Scikit-learn, or XGBoost; using AWS services including SageMaker; modeling ... Skills Agile Environments, Python (Programming Language), PyTorch, scikit-learn We believe that ...

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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
Infographic showing various Pytorch Developer job openings in Pennsylvania as of May 2026, with employment types broken down into 88% Full Time, 2% Part Time, and 10% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution.

Research Engineer (Python/Pytorch)

CSS Tec

Garnet Valley, PA • On-site

Other

Posted 6 days ago

Job description


3 days ONSITE

Job Overview: We are seeking a skilled and motivated Mid-Level Research Scientist to join our team. The ideal candidate will focus on developing and deploying multimodal machine learning models specifically for speaker identification and verification tasks. This role involves designing and refining neural architectures that encompass various features, training and evaluating deep learning models, and enhancing the robustness of these systems for real-world applications in voice authentication and behavioral analysis.

Key Responsibilities:

•Model Development: Design innovative neural architectures that integrate speech,acoustic, and linguistic features for speaker identification and verification tasks.

•Data Handling: Train deep learning models on large-scale datasets, includingparticipation in the construction and annotation of specialized datasets, such as theAmerican Dream Dataset.

•Evaluation & Benchmarking: Benchmark age prediction and speaker verificationmodels, leveraging datasets to enhance model performance and demonstrate superiorgeneralization.

•Research Prototyping: Conduct research initiatives focused on cross-modalrepresentation learning and predictive modeling of political career advancement usingvoice quality and prosodic features.

•Optimization: Optimize existing models, including the development of lightweightarchitectures for resource-constrained environments, such as real-time image captioningsystems.

•Architecture Design: Evaluate and benchmark diverse adapter architectures for vision-text alignment, while achieving state-of-the-art performance metrics on establisheddatasets (e.g., COCO dataset).

•Collaboration: Collaborate with cross-functional teams to translate research findings intoscalable solutions and real-world applications.

Required:

•Master’s or PhD in Computer Science, Electrical Engineering, or a related field.

•3-5 years of experience in machine learning and deep learning, with a proventrack record of developing multimodal models.

•Strong proficiency in programming languages such as Python and frameworksincluding TensorFlow and PyTorch.

•Experience with acoustic and linguistic feature extraction and understanding ofspeaker identification and verification systems.

•Familiarity with natural language processing (NLP) and computer visionintegrations, particularly in real-time applications.

•Strong analytical and problem-solving skills, with the ability to work independentlyand as part of a team.

•Excellent communication skills to present complex technical concepts to diverseaudiences.

Preferred Skills:

•Publications in relevant conferences or journals.

•Experience in research involving behavioral analysis and authenticationsystems.

•Understanding of model efficiency and optimization strategies for deployingmachine learning models in production.

 

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