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Tensorflow Pytorch Jobs in Columbus, OH (NOW HIRING)

Gen AI Developer Intern

Columbus, OH · On-site

$18 - $23.75/hr

... TensorFlow, Keras, PyTorch, Flask, Django, AWS Sagemaker, AWS Bedrock and Azure - ML Studio, cognitive services & OpenAI. • Understanding of ethical considerations and biases in AI systems. Skills:

Gen AI Developer Intern

Dublin, OH · On-site

$18.50 - $24.50/hr

... TensorFlow, Keras, PyTorch, Flask, Django, AWS Sagemaker, AWS Bedrock and Azure - ML Studio, cognitive services & OpenAI. • Understanding of ethical considerations and biases in AI systems. Skills:

Experience using Python machine learning and deep learning frameworks and libraries, including PyTorch, Keras, TensorFlow, scikit-learn, NumPy, and SciPy * Experience designing and implementing ...

Showing results 21-40

Tensorflow Pytorch information

See Columbus, OH salary details

$36.2K

$118.6K

$189.8K

How much do tensorflow pytorch jobs pay per year?

As of Aug 14, 2026, the average yearly pay for tensorflow pytorch in Columbus, OH is $118,553.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,100.00 and $131,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a deep learning engineer specializing in TensorFlow and PyTorch?

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 Columbus, OH?

For Tensorflow Pytorch jobs in Columbus, OH, the most frequently searched job titles are:

What cities near Columbus, OH are hiring for Tensorflow Pytorch jobs?

Cities near Columbus, OH with the most Tensorflow Pytorch job openings:

CCB Risk Modeling - AI ML Sr. Associate

JPMorgan Chase & Co

Columbus, OH • On-site

Full-time

Medical, Retirement

Posted 3 days ago

New


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 494 frontline employees who took The Breakroom Quiz

71st of 171 rated banks


Job description

The CCB Risk Modeling team is seeking talented professionals with expertise in machine learning, explainable AI (XAI), and responsible AI practices, with a focus on credit decision and fraud modeling applications. Our work centers on explainability, fairness, and algorithmic bias - understanding how modern AI systems reason and make decisions across ML systems, next-generation LLMs, and agentic workflows. The ideal candidate will drive these initiatives across model development, tooling, and cross-functional collaboration, ensuring AI/ML solutions meet ethical standards and regulatory expectations.

Key Responsibilities

  • Model Development: Design and develop machine learning models to drive impactful decisions across credit decisions and fraud modeling, covering the entire customer lifecycle, including acquisition, account management, transaction authorization, and collections.
  • Advanced Machine Learning Techniques: Apply state-of-the-art machine learning methodologies - including deep learning architecture, transformer-based models, and LLMs - on big data platforms to tackle complex business challenges.
  • Explainability & Fairness: Develop and maintain tools and frameworks that enhance AI/ML model explainability and fairness, ensuring transparency and ethical use of models.
  • Strategic Collaboration: Work closely with senior management to develop and implement ambitious, innovative modeling solutions, ensuring their successful deployment into production environments.
  • Cross-Functional Partnership: Collaborate with diverse teams, including risk, technology, model governance, and research, throughout the entire modeling lifecycle-from development and review to deployment and operational use.

Basic Qualifications

  • Ph.D. or Master's degree from a reputable institution in a quantitative discipline such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering.
  • 2 years of experience with data analysis in Python.
  • Proven track record in designing, building, and deploying high-quality machine learning models in production environments, demonstrating a strong ability to translate theoretical concepts into practical applications.
  • In-depth knowledge of advanced machine learning algorithms, including logistic regression, XGBoost, Deep Neural Networks (CNN and RNN), clustering, and recommendation systems, with expertise in model design, hyperparameter tuning, and responsible deployment practices.
  • Demonstrated experience in model interpretability and explainability for complex models such as XGBoost and GBM; experience extending these methods to deep learning architectures (CNNs, RNNs, transformers) is a strong plus.
  • Familiarity with large language models (LLMs) and their applications, including experience in fine-tuning, prompt engineering, and responsible deployment with appropriate safeguards, monitoring, and auditability.
  • Proficiency in Python, TensorFlow, PyTorch, Spark, or Scala, coupled with experience in big data technologies such as Hadoop, AWS, and Hive, and familiarity with MLOps tooling that supports model monitoring, drift detection, and end-to-end auditability.

Preferred Qualifications

  • Strong expertise, interest, and track record of performing cutting-edge research on Explainable AI

(XAI) and LLM.

  • Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is desired.
  • Strong ownership and execution; proven experience in implementing models in production.

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

We offer a broad array of credit cards to meet the needs of individuals and small businesses, including Chase-branded and co-branded cards in partnership with well-known companies and organizations. Merchant Services is a leading provider of payment, fraud and data security for companies, capable of authorizing transactions across global currencies.

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