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Tensorflow Pytorch Jobs in Greeley, CO (NOW HIRING)

BillGO, Inc.

AI Data Scientist

Fort Collins, CO

... TensorFlow, PyTorch), and data pipelines. • Strong background in supervised/unsupervised learning, anomaly detection, NLP, and generative AI. • Familiarity with financial data structures ...

BillGO, Inc.

AI Data Scientist

Fort Collins, CO · On-site

$102K - $146K/yr

... TensorFlow, PyTorch), and data pipelines. • Strong background in supervised/unsupervised learning, anomaly detection, NLP, and generative AI. • Familiarity with financial data structures ...

Sierra Nevada Corporation

Sr AI/ML Engineer

Longmont, CO · On-site

$103K - $141K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic)

Toyon

Deep Learning Algorithm Developer

Fort Collins, CO · On-site

$100K - $190K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience with PyTorch, TensorFlow, or other deep learning frameworks is required. An advanced degree (M.S./Ph.D.) or a Bachelor's degree and at least two years of industry experience are strongly ...

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Tensorflow Pytorch information

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$36K

$117.9K

$188.8K

How much do tensorflow pytorch jobs pay per year?

As of Aug 17, 2026, the average yearly pay for tensorflow pytorch in Greeley, CO is $117,932.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,600.00 and $130,700.00 per year, depending on experience, location, and employer.

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 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.

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 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.

What cities near Greeley, CO are hiring for Tensorflow Pytorch jobs?

Cities near Greeley, CO with the most Tensorflow Pytorch job openings:

Tensorflow Pytorch jobs near you

AI Data Scientist

BillGO, Inc.

Fort Collins, CO

Full-time

Re-posted 3 days ago

Job description

About the Role

We’re looking for a Data Scientist with deep AI and machine learning expertise to help shape the future of data-driven innovation in fintech. You’ll work on developing intelligent systems that power risk modeling, fraud prevention, customer insights and targeting, and payment optimization. Your models will have a direct impact on financial decisions, operational efficiency, and customer trust across our products.

Key Responsibilities
  • AI-Driven Insights: Develop and deploy advanced machine learning models to optimize customer targeting, payment monitoring and growth and operational efficiency opportunities.
  • Predictive Modeling: Build forecasting models to improve transaction accuracy, detect anomalies, and assess financial risk.
  • Data Engineering & Feature Design: Clean, transform, and model large, high-velocity financial datasets with attention to data integrity and compliance.
  • AI Product Integration: Collaborate with Product to integrate AI solutions into production systems for real-time financial decisioning.
  • Experimentation: Lead A/B tests and model performance evaluations to validate model effectiveness and regulatory compliance.
  • Communication: Translate technical findings into actionable insights for business leaders and compliance teams.
  • Research & Innovation: Stay on top of advancements in generative AI, LLMs, and financial AI applications to guide innovation strategy.

Required Qualifications
•    Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or related field.
•    3+ years of experience in a data science or AI-focused role within fintech, banking, or payments.
•    Expertise in Python, machine learning frameworks (scikit-learn, TensorFlow, PyTorch), and data pipelines.
•    Strong background in supervised/unsupervised learning, anomaly detection, NLP, and generative AI.
•    Familiarity with financial data structures, regulatory standards (e.g., PCI-DSS, GDPR), and model governance.
•    Experience with cloud platforms such as Snowflake for ML deployment.
Preferred Qualifications
•    Experience in fraud analytics, risk scoring, or payment decision models.
•    Understanding of MLOps and continuous model monitoring in regulated environments.
•    Familiarity with financial transaction data, open banking APIs, or real-time payments systems.
•    Experience developing LLM-powered assistants or AI copilots for financial operations or support.
•    Strong data storytelling and visualization skills (Tableau preferred).

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