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Tensorflow Pytorch Jobs in Kentucky (NOW HIRING)

Experience with deep learning frameworks like TensorFlow or PyTorch. * Familiarity with cloud platforms such as AWS, Azure, or GCP. * Experience with data visualization tools like Tableau or Power BI.

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

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

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

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

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

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

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

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:
Data Scientist

Other

Posted 16 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. The Project Talent Model is designed for professionals with specialized skills that align to a current client need. Team members focus on delivering services to clients, without additional expectations related to business development or promotion. Their employment is tied to their role on a project, and they are eligible for a benefits package that is competitive for project delivery-focused professionals.

Recruiting for this role ends on June 30th 2026

Work you'll do/Responsibilities

  • Work with stakeholders to identify business problems and formulate them as data science challenges.
  • Collect, clean, and explore large datasets to uncover trends and patterns.
  • Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
  • Validate and deploy models into production environments.
  • Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
  • Stay up to date with the latest trends and technologies in data science and machine learning.
  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others
  • Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
  • Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes

The Team 

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

Qualifications

 Required

  • Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
  • 5+ Years of Experience in a Data Science or Machine Learning role.
  • 5+ Years of Experience Proficiency in programming languages such as Python or R.
  • 5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
  • 5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
  • Limited immigration sponsorship may be available
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve

Preferred

  • Master's or Ph.D. in a relevant field.
  • Experience with big data technologies like Spark or Hadoop.
  • Experience with deep learning frameworks like TensorFlow or PyTorch.
  • Familiarity with cloud platforms such as AWS, Azure, or GCP.
  • Experience with data visualization tools like Tableau or Power BI.
  • Analytical/ Decision Making Responsibilities
  • Analytical ability to manage multiple projects and prioritize tasks into manageable work products
  • Can operate independently or with minimum supervision
  • Excellent Written and Communication Skills
  • Ability to deliver technical demonstrations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. 

Qualifications:

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. The Project Talent Model is designed for professionals with specialized skills that align to a current client need. Team members focus on delivering services to clients, without additional expectations related to business development or promotion. Their employment is tied to their role on a project, and they are eligible for a benefits package that is competitive for project delivery-focused professionals.

Recruiting for this role ends on June 30th 2026

Work you'll do/Responsibilities

  • Work with stakeholders to identify business problems and formulate them as data science challenges.
  • Collect, clean, and explore large datasets to uncover trends and patterns.
  • Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
  • Validate and deploy models into production environments.
  • Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
  • Stay up to date with the latest trends and technologies in data science and machine learning.
  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others
  • Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
  • Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes

The Team 

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

Qualifications

 Required

  • Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
  • 5+ Years of Experience in a Data Science or Machine Learning role.
  • 5+ Years of Experience Proficiency in programming languages such as Python or R.
  • 5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
  • 5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
  • Limited immigration sponsorship may be available
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve

Preferred

  • Master's or Ph.D. in a relevant field.
  • Experience with big data technologies like Spark or Hadoop.
  • Experience with deep learning frameworks like TensorFlow or PyTorch.
  • Familiarity with cloud platforms such as AWS, Azure, or GCP.
  • Experience with data visualization tools like Tableau or Power BI.
  • Analytical/ Decision Making Responsibilities
  • Analytical ability to manage multiple projects and prioritize tasks into manageable work products
  • Can operate independently or with minimum supervision
  • Excellent Written and Communication Skills
  • Ability to deliver technical demonstrations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. 

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