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Tensorflow Pytorch Jobs in Raleigh, NC (NOW HIRING)

Frontier Technology Inc.

AI/ML Engineer

Raleigh, NC · Remote

$140K - $220K/yr

Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain. * Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or ...

Frontier Technology Inc.

AI/ML Engineer

Durham, NC · Remote

$140K - $220K/yr

Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain. * Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or ...

Frontier Technology Inc.

AI/ML Engineer

Durham, NC · On-site +1

$140K - $220K/yr

Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain. * Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or ...

Frontier Technology Inc.

AI/ML Engineer

Durham, NC · Remote

$140K - $220K/yr

Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain. * Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or ...

Bandwidth

Sr. Data Scientist

Raleigh, NC · On-site

Expert-level proficiency in Python, with deep knowledge of the data science and ML ecosystem including pandas, NumPy, scikit-learn, TensorFlow, PyTorch, and MLflow or equivalent MLOps tooling.

Frontier Technology Inc.

AI/ML Engineer

Raleigh, NC · Remote

$140K - $220K/yr

Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain. * Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or ...

Frontier Technology Inc.

AI/ML Engineer

Durham, NC · Remote

$140K - $220K/yr

Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain. * Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or ...

Qualcomm

Senior AI Performance Architect

Raleigh, NC · On-site

$162.30K/yr

Knowledge of front-end ML frameworks (i.e.,TensorFlow, PyTorch) used for training of ML models * Strong communication skills (written and verbal) * Detail-oriented with strong problem-solving ...

Duke University

Quantitative Associate

Durham, NC · On-site

$125K - $140K/yr

Exposure to machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and techniques. * Experience with database querying (e.g., SQL). Choose Duke. Why Join DUMAC? * Impact: Play a ...

Bandwidth

Sr. Data Scientist

Raleigh, NC

Expert-level proficiency in Python, with deep knowledge of the data science and ML ecosystem including pandas, NumPy, scikit-learn, TensorFlow, PyTorch, and MLflow or equivalent MLOps tooling.

Duke University

Quantitative Associate

Durham, NC · On-site

Exposure to machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and techniques. * Experience with database querying (e.g., SQL). Choose Duke. Why Join DUMAC? * Impact: Play a ...

Bandwidth

Sr. Data Scientist

Raleigh, NC · On-site

Expert-level proficiency in Python, with deep knowledge of the data science and ML ecosystem including pandas, NumPy, scikit-learn, TensorFlow, PyTorch, and MLflow or equivalent MLOps tooling.

DPR Construction

MLOps Engineer

Raleigh, NC · On-site

Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn Required Skills * Experience ...

Duke University

Quantitative Associate

Durham, NC · On-site

$125K - $140K/yr

Exposure to machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and techniques. * Experience with database querying (e.g., SQL). Choose Duke. Why Join DUMAC? * Impact: Play a ...

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Tensorflow Pytorch information

See Raleigh, NC salary details

$36.5K

$119.3K

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How much do tensorflow pytorch jobs pay per year?

As of May 30, 2026, the average yearly pay for tensorflow pytorch in Raleigh, NC is $119,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,800.00 and $132,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Deep Learning Engineer specializing in TensorFlow and PyTorch, and why are they important?

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 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 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 Raleigh, NC? For Tensorflow Pytorch jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Raleigh, NC look for? The top searched job categories for Tensorflow Pytorch jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Tensorflow Pytorch jobs? Cities near Raleigh, NC with the most Tensorflow Pytorch job openings:
Tensorflow Pytorch jobs near you
AI/ML Engineer

AI/ML Engineer

Frontier Technology Inc.

Raleigh, NC • Remote

$140K - $220K/yr

Full-time

Posted 10 days ago

Job description

Frontier Technology Inc. (FTI) is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.

FTI delivers mission-focused solutions to the Department of Defense/Department of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.


  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.

Minimum Requirements:

  • Must be a U.S. citizen and be willing to obtain and maintain a secruity clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.

  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.

  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

 Preferred Qualifications:

  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

For this role, the compensation range is $140k-$220k.

*Note: Starting pay will be based on a number of factors and commensurate with the candidate’s residence location, qualifications & experience.

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