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Tensorflow 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 ...

Trackmind

$92K - $127K/yr

... TensorFlow, Hugging Face, Scikit-learn, Pandas, and NumPy • Implement vector search and semantic retrieval solutions using FAISS, Pinecone, or similar technologies • Fine-tune, evaluate, and ...

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 ...

Xometry

Senior Machine Learning Engineer

Lexington, KY · Hybrid

$103K - $142K/yr

Experience with large scale data processing (e.g., Hands-on experience training and applying models at scale using deep learning frameworks like PyTorch or Tensorflow) * Successful candidates in this ...

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How much do tensorflow jobs pay per year?

As of Jun 10, 2026, the average yearly pay for tensorflow in Kentucky is $106,602.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,500.00 and $118,100.00 per year, depending on experience, location, and employer.

What is a TensorFlow job?

A TensorFlow job typically involves developing, training, and deploying machine learning models using TensorFlow, an open-source AI framework. Responsibilities may include data preprocessing, building neural networks, optimizing model performance, and integrating models into applications. These roles are common in industries like healthcare, finance, and autonomous systems, requiring skills in Python, deep learning, and TensorFlow's ecosystem.

What are typical daily responsibilities for someone working in a TensorFlow Developer role?

As a TensorFlow Developer, your day-to-day responsibilities often include designing and building machine learning models, preprocessing data, conducting model training and evaluation, and deploying models to production environments. You may also work closely with data scientists, software engineers, and product managers to identify use cases, define project requirements, and optimize system performance. Regular tasks can involve using tools for data visualization, debugging, and performance tuning, as well as keeping up with the latest advancements in machine learning techniques. Collaboration and clear communication are key, as projects often require input and feedback from multiple technical and non-technical stakeholders.

What are the key skills and qualifications needed to thrive in the Tensorflow position, and why are they important?

To thrive in a TensorFlow Developer role, you need strong programming skills in Python, deep learning knowledge, and hands-on experience with TensorFlow and related AI frameworks. Familiarity with tools like Keras, TensorBoard, and cloud platforms such as Google Cloud is often required, and TensorFlow Developer certifications are highly valued. Excellent problem-solving, communication, and teamwork skills help professionals navigate complex projects and collaborate effectively with cross-functional teams. These skills and qualities ensure the successful design, deployment, and optimization of machine learning models in real-world applications.

What are the most commonly searched types of Tensorflow jobs in Kentucky? The most popular types of Tensorflow jobs in Kentucky are:
What are popular job titles related to Tensorflow jobs in Kentucky? For Tensorflow jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Tensorflow jobs in Kentucky look for? The top searched job categories for Tensorflow jobs in Kentucky are:
Tensorflow jobs near you

AI Engineer

Purple Drive Technologies

Louisville, KY • On-site

Full-time

Posted 19 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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