1

Tensorflow Pytorch Jobs in Kentucky (NOW HIRING)

Data Engineer (Remote)

Louisville, KY ยท 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)

$49 - $63.25/hr

... with PyTorch, TensorFlow, Hugging Face, Scikit- learn, Pandas, NumPy โœ”๏ธ REST API development using FastAPI or Flask โœ”๏ธ Cloud deployment experience on AWS, Azure, or GCP โœ”๏ธ Strong ...

Senior Machine Learning Engineer

Lexington, KY ยท 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 ...

Senior Machine Learning Engineer

Lexington, KY ยท On-site

$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 ...

Senior Machine Learning Engineer

Lexington, KY ยท On-site

$91K - $125K/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 ...

Strong programming skills in Python; experience with ML frameworks (PyTorch, TensorFlow) and agent orchestration tools. * Experience in business process analysis, process mapping, and workflow ...

next page

Showing results 1-20

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:
Data Engineer (Remote)

Data Engineer (Remote)

The Phia Group

Louisville, KY โ€ข On-site, Remote

$104K - $125K/yr

Full-time

Posted 15 days ago


Job description

The Phia Group is a service- oriented organization assisting employee health plans nationwide. We provide our clients with innovative cost-cutting solutions and constantly expanding service offerings. We continue to enjoy growth thanks to our most valuable resource - our talented and committed team.
At The Phia Group, whose mission is to provide high quality yet affordable healthcare to American employees and their families, you can look forward to not only unparalleled benefits for yourself but also being immersed in a company that was named one of USA Today's Top Workplaces for 2026. Meanwhile, from a regional perspective, both The Boston Globe and Louisville Business First also recognized our unwavering commitment to upholding an internal culture of inclusivity, enjoyment, and empathy for our valued employees by listing The Phia Group in their respective lists for the Top Places to Work in 2026.
The Data Engineer is responsible for supporting the development, maintenance, and optimization of data pipelines and analytics-ready datasets. You will be collaborating across multiple teams and stakeholders to solve complex problems and support data-driven initiatives.
Essential Duties and responsibilities include the following; other duties may be assigned:
  • Build, maintain, and optimize data pipelines utilizing Azure Data Factory, ensuring data is ingested, transformed, and delivered to Snowflake reliably for analytics
  • Implement monitoring, alerts, and testing of data pipeline performance, data quality metrics, and lineage to ensure trustworthy data delivery
  • Troubleshoot data issues and perform root cause analysis to proactively resolve operational issues
  • Document data structures, processes, architectural decisions, and best practices for knowledge sharing
  • Develop, maintain, and optimize Snowflake objects (schemas, tables, views) and SQL transformations to produce curated, analytics-ready datasets
  • Collaborate with analysts, stakeholders, and product owners to translate business needs into data requirements and stable technical implementations
  • Enable data for AI/ML use cases by preparing feature-rich datasets, supporting feature engineering, and ensuring data consistency for model training and inference
  • Support deployment and operationalization of machine learning models by integrating pipelines with ML workflows (e.g., batch/real-time scoring)
  • Continually improve ongoing reporting and analytics, automating or simplifying self-service or manual processes
  • Implement version control practices for all data engineering code and documentation

Experience and Qualifications
  • Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field; or equivalent experience
  • 5+ years of experience in data engineering or business intelligence roles working with ETL, data modeling, data architecture, and developing pipelines and applications for analytics (e.g., BI, reporting, machine learning, deep learning)
  • Solid programming skills in advanced SQL, Python, or other programming languages for data processing and automation

Experience supporting or working with AI/ML workflows, including:
  • Data preparation and feature engineering for machine learning models
  • Integration of data pipelines with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch, or similar)
  • Understanding of model lifecycle concepts (training, validation, deployment, monitoring)
  • Expertise working with Snowflake for data warehousing, including experience with schema design, performance tuning, and optimization
  • Proficiency with Git, Azure DevOps, and collaborative development best practices
  • Experience designing, developing, and deploying end-to-end pipelines using Azure Data Factory

Working Conditions / Physical Demands
Sitting at workstation for prolong periods of time. Extensive computer work. Workstation may be exposed to overhead fluorescent lighting and air conditioning. Fast paced work environment. Operates office equipment including personal computer, copiers, and fax machines.
This job description is not intended to be and should not be construed as an all-inclusive list of all the responsibilities, skills or working conditions associated with the position. While it is intended to accurately reflect the position activities and requirements, the company reserves the right to modify, add or remove duties and assign other duties as necessary.
External and internal applicants, as well as position incumbents who become disabled as defined under the Americans with Disabilities Act, must be able to perform the essential job functions (as listed here) either unaided or with the assistance of a reasonable accommodation to be determined by management on a case by case basis.