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Tensorflow Pytorch Jobs in Missouri (NOW HIRING)

Jobtailor

Solutions Architect, AI and ML

California, MO · On-site

$130 - $180/hr

Experience with TensorFlow or PyTorch, GPU, and CUDA * BS, MS, or PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or another Engineering field, or equivalent experience

Stackruit Ltd.

AI Software Engineer

California, MO · On-site

$136.80 - $299.30/hr

A solid understanding of AI concepts, algorithms, and frameworks (TensorFlow, PyTorch). * Knowledge of software development best practices and version control systems (Git). Benefits * Competitive ...

APC Integrated Services

AI Engineer

O Fallon, MO · On-site

$110K - $150K/yr

AI Developer Position Details Position Title: AI Developer Location: O'Fallon, Missouri (Hybrid) Company: Milestone Marketing Solutions Work Schedule: Hybrid, 4 days in office and 1 day remote ...

Jobtailor

AI/ML Software Engineer

California, MO · On-site

$95 - $135/hr

Work independently with some guidance, and review or guide activities of more junior employees Requirements * 3+ years of experience with ML software libraries such as TensorFlow, Keras, PyTorch, or ...

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Tensorflow Pytorch information

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 are popular job titles related to Tensorflow Pytorch jobs in Missouri?

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

What job categories do people searching Tensorflow Pytorch jobs in Missouri look for?

The top searched job categories for Tensorflow Pytorch jobs in Missouri are:

What cities in Missouri are hiring for Tensorflow Pytorch jobs?

Cities in Missouri with the most Tensorflow Pytorch job openings:

Tensorflow Pytorch jobs near you

Staff Machine Learning Engineer, Generative AI Modeling, Inference

Jobtailor

California, MO • On-site

$180 - $240/hr

Other

Posted yesterday

New

Job description

  • Develop innovative machine learning technology and products serving millions of Snapchatters
  • Build cutting-edge augmented reality experiences using generative models
  • Deliver generative machine learning experiences on device
  • Partner with cross-functional Snap teams to explore and prototype new products
Requirements
  • Proven passion for machine learning and staying current with research
  • Familiarity with neural networks, deep learning, and generative modeling
  • Deep understanding of mathematics and/or machine learning algorithms
  • Ability to solve open, ambiguous problems
  • Ability to collaborate effectively with internal teams and external partners
  • Ability to work independently
  • Bachelor's degree in a technical field such as computer science, mathematics, or statistics, or equivalent years of experience
  • 8+ years of post-Bachelor’s machine learning or related experience; or a Master’s degree in a technical field plus 7+ years of post-graduate ML or related experience; or a PhD in a related technical field plus 4+ years of post-graduate ML or related experience
  • Experience with computer vision or generative modeling techniques
  • Experience with TensorFlow, PyTorch, JAX, MLX, scikit-learn, or related frameworks
  • Preferred: advanced degree in computer science or related field
  • Preferred: experience training large-scale diffusion models for images, videos, or 3D
  • Preferred: knowledge of distillation, quantization, and model compression techniques
  • Preferred: knowledge of GPU, CPU, or NPU optimization techniques
  • Preferred: experience building and optimizing ML inference pipelines
Core Competencies

Demonstrates expertise in machine learning, particularly in generative modeling and deep learning, with a strong foundation in mathematics and algorithms. Proven ability to collaborate across teams and deliver innovative augmented reality experiences.

Highest-signal resume keywords
  • Machine Learning Expertise
  • Generative Modeling
  • Deep Learning
  • TensorFlow
  • Computer Vision
ATS Optimization Keywords Hard Skills
  • Machine Learning Algorithms
  • Neural Networks
  • Generative Modeling Techniques
  • Mathematics
  • Large-Scale Diffusion Models
  • Model Compression Techniques
  • ML Inference Pipelines
  • GPU Optimization
  • CPU Optimization
  • NPU Optimization
Soft Skills
  • Problem Solving
  • Collaboration
  • Independence
Industry Keywords
  • Augmented Reality
  • Generative Models
  • Cross-Functional Collaboration
  • Research in Machine Learning
Tools & Technologies
  • TensorFlow
  • PyTorch
  • JAX
  • MLX
  • Scikit-learn
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