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Tensorflow Pytorch Jobs in Delaware (NOW HIRING)

Athena LLC

TensorFlow, PyTorch, scikit-learn) and experience training or fine-tuning models. * Prior exposure to recommendation algorithms or matching systems through coursework or projects. * Familiarity with ...

Athenago

Data Science Intern

Wilmington, DE

TensorFlow, PyTorch, scikit-learn) and experience training or fine-tuning models. * Prior exposure to recommendation algorithms or matching systems through coursework or projects. * Familiarity with ...

ClifyX

GenAI Engineer

Wilmington, DE · On-site

TensorFlow, PyTorch • GenAI Tools: LangChain, LlamaIndex • Vector DB: Pinecone, FAISS • Cloud Technologies: AWS / Azure / GCP • Data Pipelines: ETL/ELT, Real-time & Batch Processing • ...

Aumni

Applied AI/ML - Vice President

Wilmington, DE · On-site

$120 - $160/hr

  • Medical

  • Retirement

Extensive hands‑on technical experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit‑learn, AWS Bedrock, Transformers, LangChain/LngGraph.

DijavAI

Machine Learning Auditor

Dover, DE · On-site

$120 - $180/hr

Experience with PyTorch, TensorFlow, and MLops tools. * Background in cybersecurity or algorithmic auditing. * Ability to explain complex technical concepts to non-technical stakeholders. * Published ...

New

Sallie Mae

Senior Manager, Statistical Modeling

Newark, DE · On-site

$85K - $104K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Proficiency in statistical programming languages such as Python, R, or SAS, and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). * Strong understanding of statistical modeling ...

JPMorgan Chase & Co.

CCB Risk Program Associate

Wilmington, DE · On-site

$135K - $165K/yr

  • Medical

  • Retirement

Proficiency in Python, TensorFlow, PyTorch, Spark, or Scala, coupled with experience in big data technologies such as Hadoop, AWS, and Hive, and familiarity with MLOps tooling that supports model ...

Berkley

Principal Engineer - AI Platform

Wilmington, DE

$131K - $175K/yr

Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn * Multiple years working with structured and unstructured data within a cloud-based data ...

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Tensorflow Pytorch information

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 are the key skills and qualifications needed to thrive as a deep learning engineer specializing in TensorFlow and PyTorch?

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.

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 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.

What are popular job titles related to Tensorflow Pytorch jobs in Delaware?

For Tensorflow Pytorch jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Tensorflow Pytorch jobs in Delaware look for?

The top searched job categories for Tensorflow Pytorch jobs in Delaware are:

What cities in Delaware are hiring for Tensorflow Pytorch jobs?

Cities in Delaware with the most Tensorflow Pytorch job openings:

Tensorflow Pytorch jobs near you
Infographic showing various Tensorflow Pytorch job openings in Delaware as of August 2026, with employment types broken down into 1% Internship, 86% Full Time, 8% Part Time, and 5% Contract. Highlights an 80% Physical, 4% Hybrid, and 16% Remote job distribution.

Senior Manager, Statistical Modeling

Sallie Mae Bank

Newark, DE • On-site

$100 - $130/hr

Other

Re-posted 7 days ago

Job description

Responsibilities
  • Design, develop and implement statistical and machine learning models and algorithms, aligning with organizational goals and digital transformation initiatives.
  • Foster a collaborative and innovative work environment that encourages knowledge sharing, professional growth, and continuous improvement.
  • Oversee the full model development and machine learning lifecycle: data collection, preprocessing, feature engineering, model development, deployment, and monitoring.
  • Collaborate with cross‑functional teams to translate business needs into effective modeling solutions.
  • Ensure models are robust, reliable, and compliant with security, privacy, and governance standards.
  • Develop and implement evaluation and validation procedures to ensure accuracy, reliability, and scalability of statistical models.
  • Generate regular reports and presentations to communicate results, insights, and recommendations to senior leadership and relevant stakeholders.
  • Stay current with advancements in machine learning and data science, and evaluate new tools and technologies for adoption.
Qualifications
  • Master’s degree in Statistics, Mathematics, Data Science, Computer Science, or a related field.
  • 5+ years of experience in statistical modeling, including hands‑on experience deploying models in production environments.
  • Proficiency in statistical programming languages such as Python, R, or SAS and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit‑learn).
  • Strong understanding of regression analysis, time‑series analysis, predictive modeling and machine learning algorithms (supervised, unsupervised, deep learning, reinforcement learning).
  • Experience with cloud‑based platforms (AWS, Azure, Google Cloud) and familiarity with data engineering, data visualization, and model evaluation techniques.
  • Excellent analytical and problem‑solving abilities, with keen attention to detail.
  • Effective communication and interpersonal skills, with the ability to present technical concepts to non‑technical audiences.
Preferred
  • Doctorate’s degree in Statistics, Mathematics, Data Science, Computer Science, Machine Learning, or a related field.
  • 8+ years of experience in statistical modeling, machine learning, or data science, including managing large‑scale ML projects.
  • Experience with MLOps, containerization (Docker, Kubernetes), and deploying models in enterprise environments.
  • Experience with data governance, security, and compliance in ML projects.

Sallie Mae is proud to be an equal‑opportunity (EEO) employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, sexual orientation, national origin, age, genetic information, gender identity, disability, veteran status, or any other characteristic protected by federal, state or local law.

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