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Tensorflow Pytorch Jobs in Kentucky (NOW HIRING)

Purple Drive Technologies

AI Engineer

Louisville, KY · On-site

Leverage frameworks such as TensorFlow, PyTorch, or Scikit-learn for model development and optimization. * Work with cloud-based AI services (Azure AI, AWS SageMaker, Google Vertex AI, etc.) for ...

Purple Drive Technologies

AI Engineer

Louisville, KY · On-site

Strong programming skills in Python (preferred), with experience in libraries such as TensorFlow, PyTorch, Scikit-learn. * Proficiency in machine learning algorithms (classification, regression ...

The Phia Group

Data Engineer (Remote)

Louisville, KY · On-site +1

$110K - $132K/yr

Integration of data pipelines with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch, or similar) * Understanding of model lifecycle concepts (training, validation, deployment, monitoring)

ADM

AI Security Architect - Erlanger, KY

Erlanger, KY

$92K - $172K/yr

Experience with ML platforms (TensorFlow, PyTorch, Scikit-learn) and MLOps tools (MLflow, Kubeflow).Familiarity with adversarial ML concepts and tools (Pyrit, IBM Adversarial Robustness Toolbox ...

The Phia Group

Data Engineer (Remote)

Louisville, KY · On-site +1

$104K - $125K/yr

Integration of data pipelines with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch, or similar) * Understanding of model lifecycle concepts (training, validation, deployment, monitoring)

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Tensorflow Pytorch information

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.

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.

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 popular job titles related to Tensorflow Pytorch jobs in Kentucky? For Tensorflow Pytorch jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Kentucky look for? The top searched job categories for Tensorflow Pytorch jobs in Kentucky are:
What cities in Kentucky are hiring for Tensorflow Pytorch jobs? Cities in Kentucky with the most Tensorflow Pytorch job openings:
Tensorflow Pytorch jobs near you

AI Engineer

Purple Drive Technologies

Louisville, KY • On-site

Full-time

Posted 20 days ago

Job description

Overview:
ob Summary:
We are seeking a highly skilled AI Applied Engineer to design, develop, and implement innovative digital solutions powered by Artificial Intelligence. The ideal candidate will bridge the gap between data science and engineering-transforming AI models into scalable, production-ready applications that deliver real-world business impact.
Key Responsibilities:
  • Design, develop, and deploy AI and Machine Learning (ML) solutions for digital transformation initiatives.
  • Collaborate with data scientists to operationalize AI models using MLOps best practices.
  • Integrate AI-driven components into existing enterprise systems and cloud platforms.
  • Build scalable data pipelines to support model training, testing, and deployment.
  • Leverage frameworks such as TensorFlow, PyTorch, or Scikit-learn for model development and optimization.
  • Work with cloud-based AI services (Azure AI, AWS SageMaker, Google Vertex AI, etc.) for large-scale deployments.
  • Apply Natural Language Processing (NLP), Computer Vision, and Predictive Analytics techniques to solve complex business challenges.
  • Partner with cross-functional teams to identify opportunities for AI automation and digital innovation.
  • Ensure solutions meet performance, scalability, and ethical AI standards.
  • Maintain detailed technical documentation, conduct code reviews, and mentor junior engineers.
Required Skills & Qualifications:
  • Strong programming skills in Python, Java, or C#.
  • Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Keras, Scikit-learn).
  • Experience deploying AI models into production environments.
  • Knowledge of MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes).
  • Familiarity with data engineering tools and ETL pipelines.
  • Understanding of cloud platforms (Azure, AWS, or GCP) and their AI/ML services.
  • Proven experience in digital transformation or intelligent automation projects.
  • Strong analytical and problem-solving abilities with a focus on innovation.
  • Excellent collaboration and communication skills.
Nice to Have:
  • Experience in Generative AI (LLMs, Prompt Engineering, LangChain, RAG frameworks).
  • Exposure to Edge AI, IoT, or Real-time analytics.
  • Familiarity with API integration and microservices architecture.
  • Knowledge of Responsible AI principles and model governance.
Education:
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.

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