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Pytorch Developer Jobs in North Carolina (NOW HIRING)

CoVar

Machine Learning Engineer

Durham, NC · On-site

PYTORCH or TensorFlow; CI/CD pipelines and regression testing • AI/ML expertise: Machine learning ... S. or Ph.D in engineering, math, computer science, or related field • Excellent technical ...

Staffingine LLC

MLOps Engineer

Charlotte, NC · On-site

MLOps Engineer Job Location: Charlotte - North Carolina - USA Job Type: Contract * 4 to 6 years of ... flow PyTorch Hugging Face Transformers and libraries like scikitlearn etc * 4 to 6 years of ...

Saransh Inc

Generative AI Architect

Charlotte, NC · On-site

$61.50 - $81/hr

Claude Microsoft GitHub Copilot PyTorch What are the top skills required for this role? 1. Hands on ... and prompt engineering frameworks 3. Participate in cross-functional GenAI initiatives and PoC ...

Euclid Innovations

ML Engineer

Charlotte, NC · On-site

Role: ML Engineer Location: Charlotte, NC 12+ months Refactor and migrate existing predictive ... Strong Python + ML frameworks (PyTorch, TensorFlow, XGBoost) * Experience with model migration ...

Tata Consultancy Services

AI/ML Engineer

Charlotte, NC · On-site

... PyTorch, Scikit-Learn, or equivalent ML frameworks. • Experience building scalable data pipelines ... AI Engineering). Company : Tata Consultancy Services is a business solutions company that ...

Tata Consultancy Services

AI/ML Engineer

Charlotte, NC · On-site

... PyTorch, Scikit-Learn, or equivalent ML frameworks. • Experience building scalable data pipelines ... AI Engineering). Company : Tata Consultancy Services is a business solutions company 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.
What are popular job titles related to Pytorch Developer jobs in North Carolina? For Pytorch Developer jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Pytorch Developer jobs in North Carolina look for? The top searched job categories for Pytorch Developer jobs in North Carolina are:
What cities in North Carolina are hiring for Pytorch Developer jobs? Cities in North Carolina with the most Pytorch Developer job openings:
Pytorch Developer jobs near you
Infographic showing various Pytorch Developer job openings in North Carolina as of July 2026, with employment types broken down into 83% Full Time, 4% Part Time, 2% Temporary, and 11% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.
Senior Data Scientist

Senior Data Scientist

Ruri Software Technologies LLC

Raleigh, NC • On-site

Full-time

Posted 25 days ago

Job description

Job Title: Senior Data Scientist
Location :Hybrid (3 days in office) - Raliegh, NC
Experience: 6 to 8 yrs
Job Description:
The Senior Data Scientist will coordinate complex cloud and artificial intelligence initiatives that leverage large language models and advanced machine learning within a hybrid work model. The role will orchestrate projects across AWS, GCP, or Azure environments, ensuring reliable Python based solutions that apply frameworks such as Keras, spaCy, and PyTorch to deliver measurable value for clients and communities.
Required Skills: Python, PyTorch, Machine Learning, Prompt Engineering, Large Language Models, AWS / GCP / Azure Cloud
Responsibilities: Develop and implement LLM based applications tailored for in house legal needs, ensuring they align with Cognizants commitment to excellence and innovation Evaluate and maintain our data assets and training evaluation datasets, ensuring they meet the highest standards of integrity and quality. Design and build pipelines for preprocessing, annotating, and managing legal document datasets, fostering a customer centric mindset. Collaborate with legal experts to understand requirements and ensure models meet domain specific needs, working as one team. Conduct experiments and evaluate model performance to drive continuous improvements, raising the bar in all deliverables. Evaluate AI ML and GenAI outcomes, both human and automated, to ensure accuracy, reliability, and alignment with business objectives. Interface with other technical personnel or team members to finalize requirements, demonstrating ownership of outcomes. Work closely with other development team members to understand complex product requirements and translate them into software designs, ensuring ethical choices in all actions. Successfully implement development processes, coding best practices, and code reviews for production environments, embodying Cognizant s values in every task. Strong hands on experience and foundations in machine learning, including dimensionality reduction, clustering, embeddings, and sequence classification algorithms. Experience with deep learning frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers. Practical experience in Natural Language Processing methods and libraries such as spaCy, word2vec, TensorFlow, Keras, PyTorch, Flair, BERT. Practical experience with large language models, prompt engineering, fine tuning, and benchmarking using frameworks such as LangChain and LlamaIndex. Strong Python background. Knowledge of AWS, GCP, Azure, or other cloud platforms. Understanding of data modelling principles and complex data models. Proficiency with relational and NoSQL databases as well as vector stores e.g Postgres, Elasticsearch OpenSearch, ChromaDB. Knowledge of Scala, Spark, Ray, or other distributed computing systems is highly preferred. Knowledge of API development, containerization, and machine learning deployment is highly preferred. Experience with ML Ops AI Ops is highly preferred. nal environments where programs span different regions, cultures, and regulatory contexts within a day shift structure
Years of Experience: 8.00 Years of Experience
Regards
Surya
Surya@rurisoft.com

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