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Pytorch Developer Jobs in New Jersey (NOW HIRING)

$118K - $142K/yr

... PyTorch). • Academic or internship experience in machine learning, AI, or data-driven projects ... engineering, and model evaluation. • Familiarity with version control (Git) and Jupyter/VS Code ...

New

Proficiency in programming languages such as Python, with experience in frameworks like TensorFlow and PyTorch. * Familiarity with natural language processing (NLP) techniques and transformer models ...

Gen AIML Expert

Iselin, NJ · On-site

$123K - $166K/yr

Partner with Product and Engineering leads to determine the technical feasibility of "moonshot" AI features 1. Languages: Expert-level Python, C++, or Java. 2. Frameworks: PyTorch, TensorFlow, JAX.

Sr. GenAI Engineer

Jersey City, NJ · On-site

$109K - $149K/yr

Familiarity with DevOps practices and tools for continuous integration and deployment. * Experience ... Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn)

... PyTorch/TensorFlow) Good to have: Cloud (Azure/AWS/Google Cloud Platform), Docker/Kubernetes Real-time systems, document AI, voice AI Profile: Strong backend engineer with hands-on AI, GenAI/LLM ...

New

... g., PyTorch, TensorFlow, scikit learn) • Experience working with LLMs, prompt engineering, or AI agent frameworks • Solid understanding of data processing and analytics using libraries such as ...

Hands on experience with AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit learn) * Experience working with LLMs, prompt engineering, or AI agent frameworks * Solid understanding of data processing ...

Sr. GenAI Engineer

Jersey City, NJ · On-site

$108K - $149K/yr

Experience with TensorFlow, PyTorch, Scikit-learn, and OpenAI API * Cloud platforms: AWS, Azure ... Familiarity with the financial services industry. * DevOps practices and Agile methodologies.

... g., PyTorch, TensorFlow, scikit learn) • Experience working with LLMs, prompt engineering, or AI agent frameworks • Solid understanding of data processing and analytics using libraries such as ...

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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 cities in New Jersey are hiring for Pytorch Developer jobs? Cities in New Jersey with the most Pytorch Developer job openings:
Infographic showing various Pytorch Developer job openings in New Jersey as of July 2026, with employment types broken down into 79% Full Time, 9% Part Time, 2% Temporary, 9% Contract, and 1% Nights. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.
Senior ML Infrastructure Engineer

Senior ML Infrastructure Engineer

Orion Innovation

Edison, NJ • On-site

$112K - $152K/yr

Full-time

Posted 22 days ago


Job description

Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.
Project Overview:
We're building a large-scale document intelligence platform that processes text files up to 5 TB in size, extracts insights using BERT-class NLP models, and surfaces answers to analysts via a low-latency query interface. The platform runs on Azure Kubernetes Service (AKS) with dedicated GPU node pools, uses KEDA for event-driven autoscaling, and integrates with Azure Data Lake Storage Gen2 and Azure OpenAI.
This is a hands-on role that sits at the intersection of platform engineering and applied ML, and requires someone who is equally comfortable debugging a CUDA out-of-memory error and designing a Kubernetes autoscaling policy. As the Senior ML Infrastructure Engineer the resource will own the end-to-end infrastructure layer - from GPU cluster configuration and CUDA runtime management to Kubernetes job orchestration and model serving.
Skill / Technology:
  • Level: Kubernetes / AKS
  • Expert: Multi-node-pool design, taint/toleration, autoscaler, GPU node pools (NC/ND series)
  • Senior: Device plugin, driver compat, resource limits, KEDA
  • Senior: Scaled Job, queue triggers, cooldown tuning, CUDA / cuDNN
  • Mid-Senior: Runtime config via PyTorch; raw kernel dev not required, PyTorch (GPU inference)
  • Senior: Batching, FP16, memory management, profiling, Hugging Face Transformers
  • Senior: BERT/DistilBERT/BGE loading, pipeline API, tokenization, Python (production)
  • Senior: Async workers, Azure SDK, queue consumers, Azure infrastructure
  • Senior: VNet, private endpoints, Key Vault, ADLS, AD, Docker / Helm
  • Senior: Multi-stage builds, Helm chart authoring, IaC (Terraform / Bicep)
  • Preferred: willingness to learn is acceptable

Orion is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, citizenship status, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
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