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Tensorflow Pytorch Jobs in Kentucky (NOW HIRING)

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 ...

Deloitte

FDE Senior Manager

Louisville, KY · On-site

Familiarity with ML frameworks (PyTorch, TensorFlow) and model evaluation. Relevant certifications - CISSP, cloud (AWS/Azure/GCP), or platform-specific IAM certifications (SailPoint, Okta, CyberArk ...

Humana, Inc.

Lead Data Scientist

Louisville, KY · On-site

Experience with machine learning frameworks like Scikit-Learn, Tensorflow, or Pytorch * Experience with high performance, large-scale ML systems * Experience with language modeling with transformers

Humana

Lead Data Scientist

Louisville, KY · On-site +1

Experience with machine learning frameworks like Scikit-Learn, Tensorflow, or Pytorch * Experience with high performance, large-scale ML systems * Experience with language modeling with transformers

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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

GenAI and Databricks Architect

Tata Consultancy Service Limited

Louisville, KY • On-site

$120K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 20 days ago

Job description

Must Have Technical/Functional Skill
• Design, delivery, and implementation of Google Cloud Platform (GCP) infrastructure and solutions.
• Architect design and implement large-scale migration pipelines from on-prem systems to Azure Data Lake Storage (ADLS).
• Architect experience in generating data pipelines in Azure ADF
• GCP Expertise: Strong knowledge of GCP AI/ML services and infrastructure.
• AI/ML Frameworks: Proficiency with TensorFlow or PyTorch.
• Technical Skills: Experience with Python, data modeling, SQL, and APIs.
• Infrastructure as Code: Experience with Terraform for automation.
• Experience: Proven ability in delivering AI/ML solutions in a cloud environment
• Experience with performing analytics on data for stakeholders.
• Experience in ingesting data from different sources using in Azure ADF
• Ensure reliable handling of high-volume unstructured data with performance and cost efficiency.
• Implement data quality checks, logging, and traceability to support audit and compliance needs.
• Experience in transforming data using Azure Databricks & Delta lake
Roles & Responsibilities
• Architecture & Design: Design enterprise-grade AI platforms, including RAG (Retrieval-Augmented Generation) and agentic solutions.
• GCP Implementation: Develop AI models using Vertex AI and Gemini, ensuring security and performance.
• Pipeline Development: Build and manage data pipelines, model lifecycle, CI/CD, and MLOps/LLMOps with Cloud Build and Vertex AI Pipelines.
• Cloud Infrastructure: Utilize GKE, Cloud Run, and BigQuery for robust application deployment.
• Strategy & Governance: Implement AI safety features, monitor model performance, and manage costs.
Salary Range: $120,000-$140,000 a year
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
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